Generic computer vision methods
1. General image segmentation methods
1. Clustering methods
2. Compression-based methods
3. Histogram-based methods
4. Region-growing methods
5. Split-and-merge methods
6. Partial differential equation-based methods
7. Graph partitioning methods
8. Multi-scale segmentation
9. Semi-automatic segmentation
10. Trainable segmentation
11. Segmentation benchmarking
2. Accumulation/voting methods
1. Hough transform
Adaptive Hough Transform
Hough transform of curves
Cascaded Hough Transform
Generalised Hough transform
Hierarchical Hough Transform
Maximum margin Hough transform
Probabilistic Hough Transform
Randomised Hough Transform
Surface finding
2. Tensor Voting
Diffusion/PDE/Time based evolution methods
1. Heat kernel -- see also scale-space which is based on linear diffusion and the Gaussian (heat
Eigendecompositions
Genetic algorithms/Genetic programming
Graph Methods
1. Graph representations
1. Adjacency graph
2. Association graph
3. Attributed Graph
4. Dynamic Feature Graph
5. Graph embedding
6. Hierarchical graph/Hypergraph representations
7. Laplacian smoothing
8. Median graph
9. Optimal Basis Graphs
10. Probabilistic graphical model, Probabilistic graph theory
2. Graph matching
1. Bayesian Graph Matching
2. Bipartite matching
3. Graph cuts
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Graph kernel methods
Graph edit distance
Maximal cliques in Association graphs
Spectral decomposition methods
Subgraph isomorphism problem
3. Multidimensional scaling
Image pyramids and scale reduction
1. Adaptive Pyramids
2. Gaussian pyramids
3. Laplacian pyramids
Level sets
1. Level set trees
Minimum description length
Multiple Scales/Resolutions
1. Multiple-scale analysis
1. Multi-Scale Integration
2. Fractals
3. Ranklets
4. Scale space
5. Wavelets
1. Noiselets
Graph, networks and connectionist methods
1. Bayesian networks
2. Connectionist methods
3. Gaussian processes methods
4. Neural networks
5. Probabilistic graphical models
1. Expectation propagation
2. Belief propagation
3. Message passing
1. Variational message passing
2. Tree reweighted message passing
6. Radial basis function networks
7. Wavelet Networks
Regularization
Relaxation
1. Continuous
2. Discrete
3. Probabilistic/Stochastic
4. Linear programming relaxation
5. Lagrangian relaxation
Spatial indexing/hashing
Subpixel Methods
Super-resolution
Certainty/uncertainty representations
1. Bayesian networks
2. Discrete (See Relaxation)
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3. Fuzzy logic
4. Intervals
5. Probabilities
18. Vision paradigms
1. Active vision
2. Geometric vision (See Vision Geometry and Mathematics and Geometric Representation of M
3. Purposive Vision
4. Qualitative Vision
19. Vision system design and characterization
1. Propagation of uncertainty
2. Performance testing in vision
3. Receiver operating characteristic
Geometric feature extraction methods
1. Compressed image feature extraction
1. Camera motion estimation
2. Color Distributions/Descriptors
3. Edge detection in compressed images
4. Salient Points
5. Texture descriptors from compressed images
2. Connected-component labeling
3. Corner and interest Point feature detectors
1. The level curve curvature approach
2. FAST: Features from the Accelerated Segment Test
3. SIFT: Scale-Invariant Feature Transform
1. David Lowe's method
4. Forstner operator
5. Haralick operator
6. Harris/Plessey Corner Finder
1. Harris affine
2. Harris laplace
7. Histogram of oriented gradients
8. Moravec operator
9. Speeded Up Robust Features (SURF)
10. Shape context, Histogram of Shape Context (HoSC)
11. SUSAN corner detector
12. Wavelet-Based salient point detection
4. Curve fitting/Local curvature estimation
1. Circle fitting
2. Curve smoothing
3. Ellipse fitting
4. Hyperbola fitting
5. Edge detection and enhancement
1. Adaptive edge detection
2. Canny edge detector
3. Color edge detectors
4. Edge types
1. Edge type labelling
5. Energy function based edge detectors
6. Evaluation of edge detectors
1. Kadir–Brady saliency detector evaluation
2. Hessian affine region detector evaluation
7. Extended edge detection
8. First derivative, Gradient edge detection
9. High-pass filter edge enhancement
10. Hueckel and other parametric fitting edge detectors
11. Kirsch compass edge detector
12. Marr–Hildreth, Laplacian of Gaussian, Zero crossing, Difference of Gaussians
13. Moving edge detection
14. Multi-dimension edge detection
15. Multi-scale edge detectors
16. Optimal edge detectors (see also Canny edge detector)
17. Sobel operator
18. Prewitt operator
19. Range/Depth image edge detectors
20. Roberts Cross edge detector
21. Robinson edge detector
22. Second derivative operators
1. Laplace operator
2. The Laplacian of Gaussian
3. Difference of Gaussians
23. Subpixel edge detection (See Subpixel methods)
24. Walsh function
6. Edge/line/Contour feature following, grouping, linking and tracking
1. Pixel connectivity
2. Contour tracking
3. Dynamic programming
4. Edge thresholding and linking
5. Graph search
6. Hough transform
7. Hysteresis tracking
8. Paired boundaries, Paired contours
9. Edge relaxation
10. Search trees
11. Subjective/Illusory contours
1. Stochastic completion fields
7. Global structure extraction
1. Ribbons
2. Interest point detection
3. Symmetry lines, Symmetry planes
8. Feature histograms
1. Histogram analysis
2. Multi-dimensional feature histograms
3. Pairwise histograms
9. Image descriptors
1. Differential invariant
Visual descriptors
MPEG-7 descriptors
Color structure descriptor
Edge histogram descriptor
Color layout descriptor
Line detection
1. Image Ridges for Line Detection
Feature mensuration
1. Scene object size estimation
2. Subpixel/Superresolution Methods (See Subpixel methods)
Model-based feature detection/segmentation
1. Mumford-Shah Functional
Point or Pixel descriptions (See also Classification transforms)
1. Bar, line points
2. Blob/center-surround points
3. Gabor filters
1. Log-Gabor filters
4. Gaussian derivatives and the notion of a visual front-end
5. Receptive fields
6. Semantic texton forests
7. Steerable pyramids
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14. Primal sketch
15. Blob and region detection
1. Bayesian network methods
2. Chroma keying
3. Facet detection
4. Maximally stable extremal regions
5. Region boundary extraction
6. Superpixels (wiktionary)
7. Texture-based region detection
16. Region detection methods
1. Divide and conquer
2. Region based, Model based segmentation
3. Recursive splitting
1. Implicit k-d tree
Region growing
Scale-space segmentation
Split and merge
Thresholding
Watersheds of gradient magnitude
Waterfall segmentation hierarchy
Ridge and valley detection
Hidden surface determination
Skew analysis and estimation
Spatial relationship detection
1. Collinearity
2. Coplanarity
3. Intersection/Cotermination
4. Relative orientation
Special feature extraction
1. Focus of expansion
2. Ground plane
3. Horizon detection
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4. Occluding contour detection
5. Vanishing point
22. Structure tensor
23. Surface patches in volumes
1. Optimal surface detection
2. Zucker-Hummel surface detection operator
24. Surface segmentation from 2 1/2D or 3D data (see also range segmentation)
1. Curvature-based surface patch detection
2. Cylinder/Tubular structure detection
3. Planar facet/triangulation patch detection
1. Marching cubes
2. Marching tetrahedrons
3. Surface fitting
4. Planar surface models
5. Surface clustering/grouping
6. Reeb graph
7. Surface discontinuity detection
1. Curvature discontinuity detection
2. Depth discontinuity detection
3. Surface Orientation discontinuity detection
8. Surface fitting/Region growing
1. Cylinder patch extraction
2. Range data based region extraction
3. Quadric fitting
4. Surface shape classification
9. Surface shape parameter estimation
1. Cylinder extraction
2. Ellipsoid/Sphere
3. Free-Form Surface
1. Dual surface thin shell fitting
4. Detection of 3D objects (Planes and cylinders)
5. Quadric
6. Torus
10. Surface Triangulation
25. Surface shape (Shape-from-X methods)
1. Shape from Contours/Silhouettes
2. Shape from defocus
3. Shape from focus
4. Shape from geometric constraints
5. Shape from multimodal integration
6. Shape from line drawings
7. Monocular depth cues
8. Structure from motion
9. Shape from multiple sensors
10. Shape from perspective
11. Shape from photo-consistency
12. Shape from photometric Stereo
13. Shape from polarization
14. Shape from shadows
15. Shape from specularities
16. Shape from structure light
17. Shape from texture
26. Image texture
1. Texture boundary detection
2. Texture classification
3. Color texture
4. Fourier descriptors
5. Hierarchical textures
6. Shape texture/surface roughness characterization
7. Structural/syntactic texture representations
8. Statistical texture representations
1. Co-occurrence matrix (texture)
2. Edge frequency
3. Law's texture energy measures
4. Filter-based descriptors
5. Fractal analysis
1. Hausdorff measure
6. Local binary patterns
7. Local ternary patterns
8. Markov random fields
9. Moments of intensity
10. Run-length encoding
11. Spatial frequency
9. Texels
1. Texon/Texel invariants and representations
10. Texture gradients/Directions/Oriented patterns
11. Wavelet-based texture descriptors
27. Topological image description
28. Visual routines, empirical feature detectors
29. Volume detection
1. Voxel-based morphometry
2. Generalized cylinder detection
3. Superquadric detection
30. Wavelet moment invariants
1. Daubechies wavelet
Geometry and mathematics
1. Basic Representations
1. Coordinate systems
1. Cartesian coordinate system
2. Cylindrical coordinate system
3. Hexagonal coordinate system (see external links)
4. Log-Polar coordinate system
5. Polar coordinate system
6. Spherical coordinate system
Digital topology
Dual space
Homogeneous coordinates
Pose/Rotation/Orientation Representations
1. Axis-angle representation
2. Clifford algebra
3. Euler angles
4. Exponential map
5. Quaternion/Dual quaternion
6. Rotation matrix
7. Pitch/Yaw/Roll
Distance metrics
1. Affine distance
2. Algebraic distance
3. Bhattacharyya distance
4. Chi-square test/metric
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5. Curse of dimensionality
6. Earth mover's distance
7. Euclidean distance
8. Fuzzy intersection
9. Hausdorff distance
10. Jeffrey divergence
11. Kullback–Leibler divergence
12. Mahalanobis distance
13. Manhattan/City block distance
14. Minkowski distance
15. Procrustes analysis
16. Quadratic form
17. Specific structural similarity
1. Curve similarity
2. Region similarity
3. Volume similarity
3. Elementary mathematics for Vision
1. Coordinate systems/Vectors/Matrices/Derivatives/Gradients/Probability
2. Derivatives in sampled images
4. Mathematical optimization
1. Golden section search
2. Lagrange multipliers/Constraint optimization
3. Multi-dimensional optimization
1. Random optimization
2. Global optimization
1. Ant colony optimization
2. Downhill simplex
3. Genetic algorithms
4. Graduated optimization
5. Markov random field optimization
6. Particle swarm optimization
7. Simulated annealing
3. Optimization with derivatives
1. Levenberg–Marquardt
2. Gradient descent
3. Quasi-Newton method
4. Model selection
5. Variational methods
5. Linear algebra for computer vision
1. Eigenfunction
2. Eigenvalues and eigenvectors
3. Principal component and Related Approaches
1. Dimensionality reduction
2. Linear discriminant analysis
3. Factor analysis
4. Fisher's linear discriminant
5. Independent component analysis
6. Kernel linear discriminant analysis
7. Kernel principal component analysis
8. Locality preserving projections
9. Non-negative matrix factorization
10. Optimal dimension estimation
11. Sufficient dimension reduction
12. Principal component analysis/Karhunen–Loève theorem
13. Principal geodesic analysis
14. Probabilistic principal component analysis
15. Rao–Blackwell theorem
4. Sammon projection
5. Singular value decomposition
6. Structure tensor
6. Multi-sensor/Multi-view geometries
1. 3D reconstruction
1. 3D shape from 2D projections
2. 3D reconstruction from multiple images
3. Slice-based reconstruction
2. Projective reconstruction
3. Baseline stereo
1. Narrow baseline stereo
2. Wide baseline stereo
4. Binocular stereo algorithms
1. Cooperative stereo algorithms
2. Binocular disparity
1. Subpixel disparity
3. Dense stereo matching approaches
4. Dynamic programming (stereo)
5. Feature matching stereo algorithms
6. Gradient matching stereo algorithms
7. Image rectification
1. Planar rectification
2. Polar rectification
8. Log-polar stereo
9. Multiresolution analysis
10. Panoramic image stereo algorithms
11. Phase matching stereo algorithms
12. Region matching stereo algorithms
13. Weakly/Uncalibrated stereo approaches
14. Spherical stereo
5. Epipolar geometry/Multi-view geometry
1. Absolute conic
2. Absolute quadric
3. Essential matrix
4. Fundamental matrix
5. Grassmannian space/Plücker embedding
6. Homography tensor
7. Transfer and novel view synthesis
8. Trifocal tensor
6. Image-based modeling and rendering
7. Plenoptic modeling
8. Image feature correspondence
1. Active stereo
2. Disparity gradient limit (feature correspondence)
3. Epipolar constraint
4. Feature contrast
5. Feature orientation
6. Grey-level similarity (feature correspondence)
7. Lipschitz continuity
8. Surface continuity
9. Surface smoothness
10. View consistency constraint
9. Scene reconstruction/Surface interpolation
1. Adaptive mesh refinement
2. Constrained reconstruction
3. Thin plate models
4. Texture synthesis/Texture mapping
5. Triangulation
6. Volumetric reconstruction
1. Visual hull
10. Trinocular (and more) stereo
7. Parameter Estimation
1. Bayesian methods
2. Constrained least squares
3. Linear least squares
4. Optimization
5. Robust techniques
8. Probability and Statistics for Computer Vision
1. Autoregression
2. Bayes estimator
3. Bayesian inference networks
4. Causal models
5. Correlation and dependence
6. Covariance and Mahalanobis distance in Vision
7. Dempster–Shafer theory
8. Multimodal distribution
9. Normal distribution
10. Heteroscedastic noise
11. Homoscedastic noise
12. Hidden Markov models
13. Probability axioms
14. Statistical hypothesis testing/Analysis of variance
15. Information theory
16. Kalman filters
1. Unscented Kalman filters
17. Canonical correlation
18. Kernel regression
19. Least mean squares estimation
20. Least median square estimation and estimators
21. Log-normal distribution
22. Logistic regression
23. Maximum likelihood
24. Model/Curve fitting
25. Monte Carlo method
26. Point process
27. Markov chain/Markov chain Monte Carlo methods
28. Markov random field
1. Applications
2. Conditional random fields
3. Multi-level Markov random fields
4. Optimization methods
1. Gibbs sampling
2. Graduated optimization
3. Graph cuts in computer vision
4. Iterated conditional modes
5. Simulated annealing
29. Mixture models and expectation-maximization (EM)
1. Gaussian mixture model
2. Categorical mixture model
30. Normalization
31. Non-parametric statistics
1. Non-parametric regression
2. Kernel density estimation
32. Poisson distribution
33. Density estimation
34. Random number generation
35. Robust estimators
9. Projective geometry/Projective transformations
1. Affine projection model/Affine transformation
2. Anamorphic projection/Catadioptric system
3. Central cylindrical projection
4. Orthographic projection
5. Map projection
6. Homography
7. Hierarchy of geometries
8. Perspective projection
9. Projective plane
10. Projective space
11. Real camera projection
12. Similarity matrix
13. Weak-perspective
1. Tomasi-Kanade factorization
10. Projective invariants/cross-ratio
1. Absolute points (points at infinity)
2. Affine invariants
1. Affine geometry of curves
3. Collineation
4. Conics/Quadrics
5. Coplanarity
6. Differential invariants
7. Duality
8. Integral invariants
9. Laguerre formula
10. Pencils
11. Quasi-invariants
12. Structural invariants
1. Cartan's equivalence method
11. Relational shape descriptions
1. Curves
1. Adjacency/Connectedness
2. Relative curvature
3. Relative length
4. Relative orientation
5. Separation
2. Regions
1. Adjacency/Connectedness
2. Relative area/size
3. Separation
3. Surfaces
1. Adjacency/Connectedness
2. Relative area/size
3. Relative orientation
4. Separation
4. Volumes
1. Adjacency/Connectedness
2. Relative orientation
3. Relative volume/size
4. Separation
12. Shape properties
1. Geometric Morphometrics
2. Kendall´s Shape Space
3. Points and local invariants
1. Scale-invariant feature transform
4. Curves and Curve Invariants
1. Affine curvature
2. Arc length
Bending energy
Chord distribution
Curvature, Torsion of a curve, Radius of curvature
Differential geometry, Frenet–Serret formulas
Invariant Points: Inflections/Bitangents
Image regions and region invariants
1. Compactness measure of a shape
2. Area
3. Perimeter
4. Center of mass, Centroid
5. Eccentricity, Elongatedness
6. Euler number/Genus
7. Extremal points
8. Feret's diameter
9. Fourier descriptors
10. Minimum bounding rectangle
11. Image moments
1. Affine moments
2. Bessel-Fourier moments
3. Binary moments
4. Color moments
5. Central moments
6. Eigenmoments
7. Fourier-Mellin moment invariants
8. Gaussian-Hermite moments
9. Texture moments
10. Hahn moments
11. Krawtchouk moments
12. Legendre moments
13. Orthogonal moments
14. Racah moments
15. Chebyshev moments
16. Zernike and velocity moments
12. Orientation
13. Sphericity
14. Rectangularity
15. Rectilinearity
16. Roundness
17. Topological invariants
1. Euler characteristic
Differential geometry of surfaces
1. Parametric surfaces
2. Common shape classes and representations
1. Cone representations
2. Cyclide
3. Cylinder representations
4. Ellipsoid/Sphere Representations
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Thin plate splines
Plane representations
Polyhedra representations
Quadric representations
Torus representations
3. Fundamental surface forms
1. First fundamental form
2. Second fundamental form
4. Gauge coordinates
5. Hessian
6. Laplace–Beltrami operator
7. Metric derivative
8. Principal curvature and directions and other local shape representations
1. Deviation from flatness
2. Gauss–Bonnet surface description
3. Gaussian curvature
4. Koenderink's shape classification
5. Mean curvature
6. Minimal surface
7. Parabolic points
8. Ridges
9. Umbilics
9. Quadratic variation
10. Ricci flow
11. Surface area
12. Surface normals and tangent planes
13. Orientability
Symmetry
1. Affine symmetry
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2. Bilateral symmetry
3. Rotational symmetry
4. Skew symmetry
8. Volumes
1. Elongatedness
2. 3D moments and moment invariants
9. Volume
13. Transformations (geometric), registration and pose estimation methods
1. Poste estimation
2. 2D to 2D pose estimation
1. Methods
3. 2D to 3D pose estimation
1. Methods
4. 3D to 3D pose estimation
1. Methods
5. Affine transformation
1. Minimal data estimation
6. Bundle adjustment
7. Euclidean transformation
1. Least-square euclidean transformation estimates
2. Minimal data euclidean transformation estimation
3. Robust euclidean transformation estimates
8. Homographic transformation
1. Least-square homography transformation estimates
2. Robust homography transformation estimates
9. Kalman filter pose estimation methods
10. Partially constrained pose
1. Incomplete information
2. Intrinsic degrees of freedom
11. Projective transformation
1. Direct linear transformation
2. Robust estimates
12. Similarity transformation
13. Articulated body pose estimation
Image physics related concepts
1. Color and reflectance
1. Albedo, Irradiance, Radiance, Reflectance, Luminance
2. Bidirectional reflectance distribution function
3. Color difference
4. Color vision, Colorimetry
1. Illumination, lightness, color constancy, reflectance recovery and shading correction
2. Color correction
3. Color normalization
5. Color representation systems
1. CIE 1931 color space
2. Color spaces and color space conversions
3. YIQ color space
4. Principal component basis space
6. Dichromatic reflectance model
7. Empirical color representations
1. Statistical colour representations
2. Basis function color representations
8. Reflectance map
9. Special worlds
1. Mondrian
2. Monochrome
2. Image content, structure and formation
1. Image content and formation
2. Neighborhood operation
3. Photometric content
1. Gamma correction
2. Hue/White balance correction
3. Quantigraphics and multiple observations
4. Saturation correction
4. Spatial frequency and sampling
5. Image quantization and compression
3. Light and illumination
1. Elementary physics of light and illumination
1. Electromagnetic radiation, Electromagnetic spectrum
2. Elementary effects: Diffraction, Interference, Reflection, Refraction, Transmittance
3. Elementary manipulation: Collimation, Diffraction gratings, Diffusion, Mirrors, Prisms
4. Standard sources: Light sources
2. Source geometry
1. Backlighting
2. Area light source
3. Diffuse reflection
4. Line light source
5. Point light source
6. Summary of different light sources
3. Special situations
1. Illumination techniques for improving observation
2. Mutual illumination and interreflections
3. Polarization
4. Shadow and highlight enhancement
5. Spectral filtering
4. Special sources
1. Acoustic Sonar
2. Infrared
3. Laser
4. Scanning electron microscope
5. Synthetic aperture radar
4. Image noise and noise in video
1. Distributions
1. Gaussian noise
2. Salt and pepper noise
3. Speckle noise
4. Uniform noise
2. Noise sources
1. Amplifier noise
2. Heteroscedastic noise
3. kTC noise
4. Electronic noise
5. Photon noise
6. Quantization noise
7. Thermal noise
5. Optics
1. Optical transfer function
2. Modulation transfer function
3. Basic geometric optics
4. Catadioptric optics
5. Depth of field
6. Depth of focus
7. Focal length
8. Focus invariant imaging
9. Image control: Focus, Aperture, Exposure/Shuttering, Gain, Offset
10. Image distortion
11. lenses
12. Telecentric lenses
13. Vignetting
6. Sensor response
7. Surface shape physics
1. Empirical surface models
2. Surface classes
1. Fractal surfaces
2. Lambertian surfaces
3. Phong reflection
4. Specular reflection
3. Texture
Image Processing Architectures & Control
Structures
1. Architectures for visual processing
1. Markup languages
2. Attention, Foveation, Saccade
1. Focus of attention
2. Gaze-contingency paradigm
3. Visual salience
3. Behavior-based control
1. Behavior-based robotics
4. Blackboard system
5. Classes of vision systems
1. Continuous process systems
2. Real-time systems/Video rate systems
3. Single image processes
6. Expert system control/Knowledge based system
7. Hierarchical control systems
1. Top-down and bottom-up systems
2. Model-based systems
8. Parallel processing
9. Sequential/Serial processing
10. Visual search
Image transformations and filters
1. Image enhancement
1. Artistic effects
2. Brightness adjustment
3. Contrast adjustment
1. Histogram equalization
2. Contrast stretching
4. Edge sharpening
5. Histogram equalization/Adaptive histogram equalization
6. Quantile normalization
7. Saturation adjustment
8. Upsampling
2. Distance and skeleton
1. Distance transform
2. Eccentricity transform
3. Laplacian eigenspace
4. Medial axis
5. Morphological skeletons
6. Topological skeletons
7. Local symmetry
8. Principal component encoding
9. Shock (mechanics)
1. Shock filter, Shock tree, Shock graph
2. Shock response spectrum
10. Smoothed local symmetry
3. Geometric transformations
1. Euclidean: Rotation, Translation, Reflection
2. Subsampling, Interpolation, zooming
3. Rectification
4. Image scaling, Shear transformation, Affine transformation, Projective transformation
5. Image warping
4. Global transforms
1. Discrete cosine/Discrete sine transforms
2. Fourier transform
1. Frequency domain filtering
2. Homomorphic filtering
3. Non-uniform Fourier transform
4. Fourier optics
5. Log-polar/Polar Fourier transform
3. Haar transform
4. Hartley transform
5. Hadamard/Walsh transform
6. Histogram transformation
1. Histogram equalization
2. Adaptive histogram equalization
3. Image histogram
4. Color histogram
7. Karhunen-Loeve transform
8. Radon transform, Mojette transform
9. Ridgelet transform
10. Slant transform
11. Modified wavefield transform
12. Trace transform
13. Wavelet transform
5. Image and Video compression
1. Adaptive coding
2. Arithmetic coding
3. Block Truncation Coding, Gif, TIFF, Lempel–Ziv–Welch, Huffman coding
4. Color image compression
5. Differential Pulse Code Modulation (DPCM)
6. Feature extraction from compressed images
7. Fractal compression
8. Hierarchical compression
9. Lossy compression
10. Lossless compression
11. Image quality evaluation/comparison
12. JPEG
13. PNG
14. Model-based coding
15. Motion coding, Video coding
16. MPEG
17. Predictive methods
18. Stereo image compression
19. Vector quantization
20. Wavelet/Scalar quantization
6. Image stabilization
7. Local operator transforms
1. Adaptive filtering
2. Composite filtering
3. Convolution
1. Normalized convolution
2. Separable templates
1. Gaussian blur
4. Difference of Gaussians
5. Differentiation filtering
6. Frequency filtering
1. High-pass filter
2. Low-pass filter
3. Matched filter
7. Image noise reduction and restoration
8. Adaptive smoothing
1. Anisotropic filtering
2. Anscombe transform
3. Moving average smoothing
4. Bayesian filtering
5. Bilateral filtering
6. Brightness distortion correction
1. Helicon filter
7. Conservative smoothing
8. Crimmins smoothing
9. Deconvolution
10. Diffusion methods
1. Diffusion equation
2. Anisotropic diffusion
11. Edge-preserving smoothing
12. Gaussian smoothing
13. Global filters
1. Tikhonov regularization
2. Maximum entropy methods
14. Kalman filter based noise reduction
15. Alpha beta filter
16. Phase-locked loop
17. Kuwahara filter
18. Bayer filter
19. Lee's local statistics filter
20. Local nonlinear image restoration
21. Median filtering
22. Median flow filtering
23. Median least variance/Median coefficient of variation filters
24. Markov chain Monte Carlo
25. Multispectral images
1. Multichannel/Multispectral filtering
26. Exponential smoothing
27. Partial Differential Equations (PDEs), Diffusion methods
1. Geometric flow, Ricci flow
2. Tangential diffusion
28. Order statistic filters
29. Savitzky–Golay smoothing filter
30. Scale space filter
31. Spline smoothing
32. Temporal averaging
33. Wiener filter
8. Morphological transformations
1. Binary mathematical morphology
2. Boolean convolution
3. Conditional dilation
4. Dilate/Erode transformation
5. Fuzzy morphology/Soft morphology
6. Grayscale morphology
1. Grayscale dilation, Grayscale erosion, Umbra dilation, Umbra erosion
2. Greylevel, Greyscale morphological opening, closing
1. Opening
2. Closing
7. Morphological smoothing
8. Morphological gradient
9. Morphological laplacian
10. Hit-or-miss transform
11. Morphological segmentation
12. Morphological opening, Morphological closing
13. Region-filling, Propagation
14. Thinning, Thickening
15. Top-hat transform
16. Watershed transform
9. Pixel classification
1. Color, Multispectral based
2. Curvature, Shape based
3. Edge type labeling
4. Intensity based
5. Shadow type labeling
6. Texture based
10. Point binary image operator transforms
1. Image arithmetic
1. Image operators: Addition
2. Image operators: Bitshift
3. Image operators: Blending
4. Image operators: Division
5. Image operators: Multiplication
6. Image operators: Subtraction
2. Binary operations
1. Image operators: AND/NAND
2. Image operators: NOT/INVERT
3. Image operators: OR/NOR
4. Image operators: XOR/XNOR
11. Point unary image operator transforms
1. Clipping
2. Pixel logarithm and exponential
3. Gamma correction
4. Ordinal transformation
5. Thresholding
1. Adaptive thresholding
2. Edge image thresholding
3. Balanced histogram thresholding
4. Multiband thresholding
5. Quantization techniques
6. Threshold selection
12. Segmentation, Grouping transforms
1. Property basis
1. Chroma keying
Intensity based segmentation (See Region detection -> thresholding)
Motion based segmentation (See Motion field->Region segmentation/decomposition)
Surface shape based segmentation (See Curvature-based surface patch detection)
Texture based segmentation (See Texture-based region segmentation)
Structures
1. Curve segmentation (See Boundary/Line/Curve segmentation)
2. Blob detection
3. Surface segmentation (See Surface segmentation from 2 1/2D or 3D data)
4. Volume segmentation
Technologies
1. Clustering based segmentation
2. Connected components/Blob extraction
3. Model based feature detection/Model based segmentation
4. Minimum description length
5. Region growing based segmentation
6. Relaxation labeling
7. Rule-based/Expert-system based segmentation
8. Thresholding based segmentation
2.
3.
4.
5.
2.
3.
Introductory visual neurophysiology
1. Crossmodal linkages
1. Audition
1. Sensory substitution
2. Olfaction
3. Touch
4. Sensory substitution
5. Mirror neuron
6. Language
1. Audio-visual speech recognition
7. Synesthesia, Neural basis of synesthesia
2. Neurophysiological methods
1. Disturbances and disorders
1. Lesion
2. Scotoma
3. Blind spot
4. Binasal hemianopsia
2. Bitemporal hemianopsia
3. Color blindness
1. Achromatopsia
2. Dichromacy
3. Monochromacy
4. Agnosia
1. Visual agnosia
2. Auditory agnosia
3. Color agnosia
5. Staining/Histology
6. Electrophysiology
1. Intracellular recording
2. Extracellular recording
3. Iontophoresis
7. Neuroimaging
1. Optical imaging of intrinsic signals
2. Calcium imaging
3. Photofragment-ion imaging
4. Voltage-sensitive dye imaging
5. Functional Magnetic Resonance Imaging (fMRI)
1. Haemodynamic response
2. BOLD response
6. Positron emission tomography (PET)
7. Single-photon emission computed tomography (SPECT) or (SPET)
8. Electroencephalography (EEG)
9. Transcranial magnetic stimulation (TMS)
10. Magnetoencephalography (MEG)
11. Molecular biology
12. Genetics
13. Neuropharmacology, Neuropsychopharmacology
3. Visual system structure
1. Neurons
2. Visual pathway
1. Dorsal and ventral stream
2. Modularity of mind
1. Visual modularity
2. Language module
3. Cortical column
4. Neural coding
5. Receptive fields
6. Extra-classical receptive fields and surround modulation
7. Topographic maps
8. Binding & Synchronization
1. The binding problem
2. Neural binding
3. Neural oscillations
9. Cortical magnification
10. Lateralization of brain function
11. Attention
4. Visual system components
1. Neuroanatomy
2. The eye
1. Structure and anatomy
2. Function
3. Eye movements
1. Saccades and Microsaccades
3. The retina
1. Development
2. Anatomy and Structure
3. Blind spot
4. Fovea
5. Circuitry
1. Photoreceptors
2. Horizontal cells
3. Bipolar neurons/cells
4. Amacrine cells
5. Ganglion cell
6. Glial cell
4. Function and computations
1. Light and dark adaptation
2. Lateral inhibition
3. Color vision
5. Lateral Geniculate nucleus (LGN)
1. Development
2. Anatomy and structure
3. Function and computations
4. Parvocellular and Magnocellular pathways
6. Visual cortex
1. Plasticity and development
1. Neuroplasticity
2. Synaptic plasticity
3. Spike-timing-dependent plasticity
4. Hebbian theory
5. Long-term potentiation
6. Long-term depression
2. Primary visual cortex (V1)
1. Anatomy and structure
2. Neuron types
1. Pyramidal cells
2. Granule cells
3. Connectivity
4. Simple cells, Complex cells, Hypercomplex cells
5. Neural coding
6. Parvocellular and Magnocellular pathways
7. Cortical layers
8. Contrast sensitivity
9. Selectivity and mapping of stimulus features
1. Ocular dominance
2. Geniculate ganglion
3. Orientation
4. Direction
5. Spatial frequency
6. Colour
7. Binocular vision
3. Extrastriate cortex, Brodmann area 18, Brodmann area 19
1. V2
2. Visual cortex#Third visual complex, including area V3
1. Dorsomedial area
2. Ventral tegmental area
3. V4
4. Dorsal Prelunate (DP)
5. V5/MT
4. Higher visual cortical areas
1. Medial superior temporal area
2. Parietal lobe
1. LIP (Lateral intraparietal)
2. VIP (Ventral Intraparietal)
3. MIP (Medial Intraparietal)
4. AIP (Anterior Intraparietal)
5. CIP (Caudal Intraparietal)
3. Brodmann area 7
4. Inferotemporal cortex
5. Broadman area 22
6. Cuneus
7. Superior Frontal Sulcus (SFS)
8. Superior temporal sulcus
9. Frontal Eye Fields (FEF)
7. Superior colliculus
8. Pulvinar nuclei
9. Caudate nucleus
Introductory visual
psychophysics/psychology
1. Attention
2. Subjective constancies
1. Color constancy
2. Lightness constancy
3. Shape constancy
4. Size constancy
5. Distance constancy
6. Location constancy
3. Disorders/disturbances
1. Aniseikonia
2. Achromatopsia
3. Scotopic sensitivity syndrome
4. Blindness
Acquired vision
Blindsight
Change blindness
Color blindness
Repetition blindness
5. Visual agnosias
1. Apperceptive agnosia
2. Associative agnosia
3. Color agnosia
4. Mirror agnosia
5. Prosopagnosia
Design of experiments
1. Detection theory
2. Fourier analysis
3. Interstimulus interval
4. Psychometric function
5. Spatial frequency
6. Statistics
7. Stevens' power law
8. Temporal frequency
9. Weber–Fechner law
Experimental stimuli
1. Autostereograms
2. Gratings
3. Optical illusions
1. Motion aftereffects
2. Ambiguous picture
3. Illusory contours
4. Random dot stereograms
5. Rapid Serial Visual Presentation (RSVP)
6. Phantom eye syndrome
Eye movements
1. Saccades and Microsaccades
2. Vestibulo-Ocular Reflex (VOR) and Pursuit movement
General concepts
1. Adaptation
2. Aftereffects
3. Contrast sensitivity
4. Saccadic suppression
5. Temporal resolution
1. Change blindness
2. Flicker fusion
6. Visual acuity
Perception
1. Color perception
1. Scotopic vision
2. Unique hues
1.
2.
3.
4.
5.
4.
5.
6.
7.
8.
2. Depth perception
1. Accommodation
2. Binocularity
3. Color depth
4. Convergence
5. Distance fog
6. Horopter
7. Occlusion
8. Parallax
9. Peripheral vision
10. Retinal disparity/Stereopsis
3. Face perception
4. Motion perception
1. Optical flow
2. Structure from motion
3. Time to contact(see depth from motion)
4. Vection
5. Multimodal perception
1. Synesthesia
6. Object Perception
1. Object recognition in cognitive neuroscience
7. Space perception
8. Texture perception
9. Perceptual organization
1. Figure–ground determination
2. Gestalt laws of grouping
10. Psychophysical methods
1. Discrimination
2. Forced choice methods
3. Just-noticeable difference
4. Method of adjustment
5. Method of constant stimuli
6. Method of limits
7. Staircase procedures
8. Thresholds
11. Theoretical perspectives
1. Affordances
2. Gestalt theory
3. Gibson's theory
4. Marr's theory
5. Unconscious inference
12. Visual search
13. Visual short term memory
Motion and time sequence analysis related
concepts
1. Active vision
1. Kinetic depth
2. Image stabilization
3. Surface reconstruction
4. Time to contact
5. Visual servoing
2. Appearance change analysis
3. Change and moving object detection
1. Background modelling
1. Finger tracking
2. ViBE algorithm
2. Change detection in compressed image/video data
3. Change detection in non-standard images: Panoramic, Omnidirectional
4. Detection with a changing background
5. Foreground modelling
6. Image differencing
7. Moving camera change detection
8. High-speed cameras
9. Shadow removal, Moving shadow detection
1. The Stauffer and Grimson algorithm
4. Depth/Range image temporal sequence analysis
5. Image sequence fusion
1. Image mosaics
2. Image stabilization
3. Super-resolution
6. Motion field
1. Depth estimation
2. Edge/Discontinuity detection
3. Hierarchical motion field estimation
4. Region segmentation/decomposition
1. Motion layer/Multiple motion segmentation
5. Particle image velocimetry
7. Motion property estimation
1. General motion estimation
2. Observer motion, Egomotion estimation
3. Periodicity estimation
4. Planar motion estimation
5. Instance centre of rotation
6. Pure translation
7. Linear motion estimation
8. Non-rigid motion analysis
1. Human pose and motion estimation
9. Optical flow
1. Affine flow
2. The aperture problem
3. Methods for determining optical flow
1. Area based methods
2. Binocular methods
3. Contour based methods
4. Correlation based optical flow estimation
5. Gradient based optical flow estimation
6. Feature based optical flow estimation
4. Optical flow boundary, discontinuity estimation
5. Color optical flow
6. Optical flow field calculation
7. Optical flow histogram
8. Information extraction
1. Egomotion estimation
2. Epipole location
3. Focus of expansion
4. Obstacle detection
1. Parking sensors
9. Multigrid methods
10. Normal flow
11. Optical flow constraint equation
12. Optical flow smoothness constraint
13. Range flow
14. Scene flow/Surface motion
15. Structure from optical flow
10. Sensor, Camera Motion estimation
11. Spatio-Temporal reasoning
1. Epipolar plane analysis
2. Spatio-temporal corner/Interest point detector
3. Spatio-temporal filters
1. Singular spectrum analysis
4. Representations
1. Small motion models
5. Temporal shape matching
1. Spatio-Temporal Relationship Match (SRM)
2. Temporal geometric shape model matching
3. Temporal property model matching
6. Temporal spatio-velocity transform
12. Structure from motion/Structure and motion
1. Articulated object segmentation
2. Classical structure from motion
3. Model-based (facial) motion capture/Model-based shape capture
4. Multi-frame structure estimation
1. Critical motions
2. Initialization
3. Euclidean reconstruction
5. Nonlinear recursive methods
6. Rigid bodies
1. Rigid body segmentation
7. Rigidity constraint
1. Kruppa equations
8. Structure consistency constraint
9. Structure factorization
1. Tomasi–Kanade factorization
2. Factorization with uncertainty
10. Temporal factorization
13. Temporal event analysis
1. Activity analysis
1. Temporal action segmentation
2. Instantaneous activity recognition
3. Long term activity
1. Hidden Markov Model matching
2. Hidden Semi-Markov Model matching
3. Rule-based/Syntactic model matching
4. Trajectory model matching
2. Novelty detection
3. Self-similarity matrix
14. Tracking
1. Articulated object tracking
2. Binocular tracking
3. Discontinuous events tracking
4. Feature tracking approaches
1. Contour tracking, Active contour tracking
2. Appearance-based tracking
3. Edge tracking
4. Fiduciary marker tracking
5. Optical flow-based target tracking
6. Pose based tracking
7. Feature-based tracking
8. Template-based tracking
9. Temporal stereo tracking
10. Texture-based tracking
5. Moving camera based tracking
6. Multiple target tracking
1. Feature-based tracking
2. Optical flow analysis
3. Template-based tracking
7. Tracking information fusion
1. Condensation/Particle filter tracking
2. Tracking using Bayesian belief propagation
3. Tracking using hidden markov models
4. Tracking using Kalman filters
8. Vergence maintenance
Non-sequential realization methods
1. Systolic arrays
1. Digital signal processing/Digital signal processor
2. Artificial neural networks
3. Hopfield networks
4. Kohonen networks
5. Perceptron networks
6. Radial basis function networks
7. Support vector machines
2. Parallel processing approaches
1. Multiple Instruction Multiple Data (MIMD)/Multiprocessing
1. Data parallelism/Domain decomposition methods
2. Single Instruction Multiple Data (SIMD)
1. Massively parallel systems
3. Vector processors
3. Programmable logic approaches
1. Reconfigurable computing
4. VLSI approaches
1. Vision chips
Object, world and scene representations
1. Full object representations
1. Flat
2. Hierarchical, by parts, structural decomposition, subcomponent representation
3. 3D object representations
2. Functional representations
3. Geometric representation of model features
1. CAD representations
2. Curve representations
1. Chain codes
2. Circles
3. Conics
4. Methods of contour integration
5. Crack codes
6. Curvature primal sketch
7. Curvature scale space
8. Cross section functions
9. Edgelet, Contourlet
10. Ellipse representations
11. Intrinsic equations
12. Line representations
13. Line moments
14. Phi-S curves, tangent angle functions
15. Polyline, Polycurves, Polygonal approximations
16. Radius vector functions
17. Signatures
18. Active contour models/Snakes
1. Gradient Flow Vector (GFV) snakes
19. Spline Representation
20. Superellipse representations
21. Supershapes
22. Support functions
23. Torsion of a curve
24. Torsion scale space
25. Wavelet descriptors
26. Width functions
3. Geometric representation of model features/Points
1. Symplectic geometry
2. Local scale descriptions
3. Point distribution models
4. Non-linear point distributions
5. Surflet
4. Region representations
1. Convex hull
2. Region cross section functions
3. Delaunay triangulation/Voronoi diagrams
4. Grey-level distribution models
5.
6. Occupancy grids
7. Polygon mesh
8. Trees
1. Octrees
2. Quadtrees
5. Surface representations
1. Algebraic point set surfaces
2. Conformal mapping
3. Local point/patch representations
4. Mean and Gaussian curvature
5. Rubbersheeting
6. Thin plate splines
7. Algebraic topology
8. Planar patches/faces, Edges, Vertices, Boundary representations
9. Principal curvature sign classes
10. Bézier surface
11. Sparse grid
12. Spherical images
13. Subdivision surface
14. B-spline
15. Surface triangulation, Surface meshes
6. Object centered representations
1. Generalized cones
2. Geon structural description
7. Objects/Volume representations
1. 3D skeletons
2. Aspect graph matching
3. Balloons
4. Constructive solid geometry
5. Set-theoretic modeling
6. Spheres
1. Surfaces of constant Gaussian curvature
2. Schwarzschild coordinates
7. Extended Gaussian Images
8. Generalized cylinders
9. Cones
10. Medial surfaces
11. Quadrics
12. Hyperquadrics
13. Superquadrics
14. Shape histogram
1. Local Energy-based Shape Histogram (LESH)
15. Spin images
1. Spherical spin images
16. Spherical harmonics
17. Supershapes
18. Boundary representation
19. Tetrahedral representations
20. Volumetric frequency
21. Voxels, Octrees
22. Wire-frame representations
4. Logical and symbolic representations
1. Frames
2. Knowledge representation
1. Description logic
2. KRL
3. Predicate calculus
1. Predicate logic
2. First-order logic
4. Relational model
5. Semantic nets
5. Multi-scale representation approaches
1. Fractals
2. Scale space
3. Wavelets
6. Non-rigid model representations
1. Active appearance models
2. Active shape models
3. Implicit shape models
4. Point distribution models
5. Deformable shapes
1. Active contour models
2. Deformable surfaces
3. Deformable volumes
6. Structural rigidity
7. Time-varying meshes
7. Non-symbolic representations
1. Eigenspace representations
2. Interest points
3. Intrinsic images
4. Light fields, Image-based modeling and rendering
8. Procedural representations
1. Production rule representations
2. Visual routines
9. Shape classes/Shape families
10. Temporal representations
1. Short-term activity representations
1. Motion history/Energy models
2. Volume motion templates
2. Long-term activity representations
1. Global representations
1. Hidden Markov models/Finite state models
2. Target trajectory models
11. Types of models
1. Active appearance models
2. Color appearance models
3. Geometric models
4. Graph models
1. Exponential random graph models
5. Relational models
12. Viewer centered representations, Viewpoint-dependent representations
1. Iconic image models
2. Aspects/characteristic views
3. Tesselated viewsphere approximations
1. Geodesic domes
Recognition and registration methods
1. Statistical classification methods
1. Bayesian classifier
2. Contextual image classification
3. Decision trees
4. Learning classifier systems
5. Feature-based
6. Fuzzy classification
7. Hough forest
8. k-nearest neighbor classification
9. Linear and higher order discriminant functions
10. Markov random field based classification
11. Minimum distance estimation
12. Multi-classifier fusion
13. Neural networks
14. Sparse coding
15. Vector quantization based classification
2. General reasoning methods used in vision
1. Ambiguous images
3. Geometric model matching, Feature correspondence, Shape correspondence
1. General matching control and search algorithms
1. Hypothesize and test
2. Heuristic search
3. Recognition by components
4. Interpretation trees and other search tree variations
5. Rule-based systems
6. Theorem proving
7. RAST algorithms
2. General recognition methods
1. Appearance-based, Iconic, View-based recognition
2. Boltzmann machine, Hopfield net, Simulated annealing
3. Constraint-based matching
4. Context-based matching
5. Template matching, Elastic matching, Deformable template
6. Geometric hashing
7. Image stitching
8. Image registration
9. Inverse compositional method
10. Iterated closest point/Iterative closest point
11. MAPSAC
12. Model based recognition
13. Multi-scale contour segmentation
14. Non-rigid alignment
15. Object categorization
1. Cognitive neuroscience of visual object recognition
2. Bag of words
3. Structured models
4. Subcategory recognition
5. Vocabulary trees
16. Object Size/Scale/distance estimation
17. Polygon matching
18. Pose clustering
19. RANSAC
20. Relaxation labeling
21. Softassign algorithm
22. Structural description
23. Template and cross-correlation matching
4. Identity verification/alignment
1. Geometric feature proximity
2. Pose consistency
5. Model based indexing, invocation
6. Special feature matching
1. 2D to 2D point feature matching
1. Proximity matrices
2. 2D to 3D point feature matching
3. 3D to 3D point feature matching
4. 2D, 3D point to structure matching
5. Aspect graph matching
6. Boundary/contour/curve/edge matching
1. TERCOM
7. Line matching
8. Phase matching
9. Property-based matching
10. Optical/Appearance flow matching
11. Polygon matching
12. Needle-map matching
13. Region matching
14. Spatial pyramid matching
15. Surface matching
16. Texture classification
17. Texture matching
18. Volume matching
7. Syntactic pattern matching
1. 1D/String matching
2. 2D/Pattern grammars
Scene understanding/image analysis
methods
1.
2.
3.
4.
Situated cognition
Affordance
Appearance prediction
Figure-ground separation
5.
6.
7.
8.
9.
10.
11.
12.
13.
High-level vision
Light source detection
Line labeling
Occlusion understanding and recovery
Perceptual organization, Perceptual grouping
1. Hierarchical organization
2. Subcomponent detection
Types of scenes
1. Manhattan world scenes
Region labeling
Scene completion
Shadow understanding
Sensor fusion, registration and planning
methods
1. Sensor fusion and registration types
1. CT scan, MRI, fMRI, NMR, PET scan
2. Structure from motion
3. Kinetic depth
4. Range and intensity
1. High dynamic range imaging
5. SAR, Digital maps
6. Visible and infrared
1. Visible spectrum
2. Infrared spectrum
3. MVIRI
2. Information fusion
3. Multi-image intensity image registration
4. Multi-view range data registration and fusion
5. Next view planning/prediction
6. Sensor networks
1. Sensor networks calibration
2. Distributed target tracking & fusion
7. Sensor path planning
8. Simultaneous Localization And Mapping (SLAM)
9. Static sensor placement/parameter determination
1. Multidimensional sampling
10. Fusion Using Kalman Filters
System models, calibration and parameter
estimation methods
1. Camera calibration
1. Camera pose estimation
1. Camera auto-calibration, Camera self calibration, Closure phase
1. Critical motions, relations, scenes
2. Zoom lens calibration
2. Camera calibration using calibration targets
2. Monocular camera calibration
3. Camera resectioning
2. Eye–hand coordination and calibration
3. Illumination field calibration
4. Image distortion, models and correction
1. Chromatic aberration
2. Defocus aberration
3. Diffraction/Interference fringes
4. Ringing artifacts
5. Fisheye lens
6. Radial lens distortion
7. Underwater lens calibration
5. Pinhole camera, intrinsic and extrinsic camera models
6. Radiometric calibration
7. Structured light source calibration
Visual learning related methods and
concepts
1. Observational learning
1. Discrete observational learning
2. Probabilistic observational learning
2. Geometric feature learning
3. Joint natural language and image data learning
1. NLP learning techniques
4. Learning technologies
1. Bayesian learning/Probabilistic model learning
1. Bayesian principal component analysis
2. Latent variable learning
3. Variational Bayesian methods
2. Clustering
1. Fuzzy clustering
2. Clustering coefficient
3. Hierarchical clustering
4. k-means clustering
1. Hierarchical k-means clustering
5. Mean-shift clustering
6. Neural gas clustering
7. Parametric/Non-parametric clustering
8. Pattern matrices
9. Proximity matrices
10. Self-organizing feature maps/Kohonen maps
11. Superparamagnetism clustering
3. Gaussian mixture models, Expectation-Maximization (EM)
4. Ensemble learning
1. Bootstrap aggregating
2. Boosting
1. AdaBoost
2. DenseBoost
3. TextonBoost
3. Extremely random trees (Extra-trees)
4. Random forests
5. Vector boosting
5. Feature selection
6. Gaussian process learning and classification
7. Genetic programming/Genetic algorithms
8. Neural networks
9. Principal component analysis
10. Support vector machines
1. Kernel methods
2. Kernel trick
3. Structured SVM
4. Relevance vector machine
11. Semi-supervised learning
12. Vector quantization
5. Shape model learning
1. Range data fusion
2. Space carving
3. Structured learning
1. Architectural models
4. Volumetric model recovery
5. Voxel coloring
1. Marching cubes
6. Property learning
1. Spatio-temporal patterns
Calendar of Computer Image Analysis, Computer Vision
Conferences
Organization and Updates of the Conference Entries
File Last Updated: 01/10/2014 00:24:41
Copyright © © 2013
Jump to the Current Week
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which should have the most up to date information for that meeting. The Call
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Thu Jan 9
no more updates until February Due to
travel
Thu Jan 9
Video Networks Extension CVIU
Special
IV Extension
Sat Dec
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Mobile Vision Sensor Special Issue
SISE
Fri Dec
20
CIARP
VIEW
ICCV 2017 Location
EMRICMR Workshop
MIUA
ICCVIA
MVML
MHCI
Medical
Imaging Summer
School
ICPRAM Doctoral
Consortium
Mon Dec
IR2S ICMR Workshop
9
Sat Dec 7 Image CLEF, Life CLEF
Mon Dec
CV Summer School
2
Mon Dec
THUMOS Info, ICCV Workshop
2
Color
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Session
Mon Nov
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2014
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P: 31 _
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Januar Februar Marc Apri Ma Jun Jul Augus Septembe Octobe Novembe Decembe
201
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2015 (Partial) Monthly Conference Calendar
P indicates paper due date. Check the full listing for other meetings, workshops assoicated with major
conferences, and special issues.
2015
Due
January February March April May June July August September October November December
2014
CVPR
P:
_
TBD
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12
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CAIP
P:
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TBD
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ICCV
P:
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TBD
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_
_
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_
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7-13
2015
Due
January February March April May June July August September October November December
2014
2016 (Partial) Monthly Conference Calendar
P indicates paper due date. Check the full listing for other meetings, workshops assoicated with major
conferences, and special issues.
2016
CVPR
2016
Due
January February March April May June July August September October November December
2015
_
_
_
_
_
TBD _
_
_
_
_
_
Due
January February March April May June July August September October November December
2012
Paper Deadlines for the Major Computer Vision Meetings.
See the chart above for more or the full listing for even more meetings.
What is
required
Deadline
Name
Conference Date
Location
Past: November 1, 2013
Full Paper
CVPR 2014
June 17-19, 2014
Columbus, Ohio
Past: December 20,
2013 Exentsion
Full Paper
ICPR 2014
August 24-28, 2014
Stockholm,
Sweden
March 7, 2014
Register
Abstract
ECCV 2014
September 5-12,
2014
Zurich,
Switzerland
June 15, 2014
Paper
ACCV 2014
Singapore November
1-4, 2014
May 2, 2014
Registration
BMVC 2014
September 1-5, 2014 Nottingham UK.
The deadlines below have passed. Wait until next year for these.
Past: April 12, 2013
ICCV 2013
December 1-8, 2013 Sydney, Australia
Past: September 2, 2013
WACV 2014,
WACV PETS,
WRV, UCCV)
March 24-26, 2014
Steamboat
Springs, CO
Past: September 21, 2012
FG 2013
April 22-26, 2013
Shanghai, China
ICIP 2013
September 15-18,
2013
Melbourne,
Australia
Past: February 5, 2013
Full Paper
Paper
2014
January 2014
Show this month on a map
International Conference on Computer Vision Theory and Applications
Lisbon, Portugal
Conference Venue
VISAPP 2014
January 5-8, 2014
Paper deadline: Past: September 18,
2013 Extension (2)
Call for papers.
January 5-8, 2014
Position Paper deadline: Past: October 15, 2013
Call for Position papers.
2nd International Conference on Photonics, Optics and Laser Technology
PHOTOPTICS
2014
January 7-9, 2014
Lisbon, Portugal
Conference Venue
Paper deadline: Past: July 2, 2013
Call for papers.
International Conference on MultiMedia Modeling
MMM 2014
January 8-10, 2014
January 6-8, 2014
Dublin, Ireland
Guinness Storehouse
Paper deadline: Past: August 9, 2013 Extension
Call for papers.
The Third International Video Browser Showdown
Competition (VBS21014)
Paper deadline: Past: September 16, 2013 Call for
Demos
1st Winter School on Multimedia Processing and
Applications (WMPA 2014)
Registration deadline: Past: September 16, 2013 Call
for Participation
February 2014
Show this month on a map
Photonics West
Photonics West
San Francisco, CA
2014
February 1-6, 2014
Paper deadline: Past: July 22,
2013
Conference Venue
Call for papers.
Annual Interdisciplinary Conference
AIC 2014
Jackson Hole, Wyoming
Teton Village
February 2-7, 2014
Paper deadline: Past: September
20, 2013
Call for papers.
EuroCOW the Calibration and Orientation Workshop
EuroCOW 2014 Barcelona, Spain
February 12-14, 2013
Paper deadline: Past: July 24,
2013
Castelldefels
Call for papers.
The Sixth International Conferences on Advances in Multimedia
MMEDIA 2014 Nice, France
February 23-27, 2014
Conference Venue
Paper deadline: Past: September
28, 2013
Call for papers.
March 2014
Show this month on a map
International Conference on Signal and Imaging Systems Engineering
SISE 2014
March 2, 2014
BIOSIGNALS
2014
March 3-6, 2014
Coimbatore, India
Conference Venue
Paper deadline: February 15, 2014 Call for papers.
7 th International Conference on Bio-inspired Systems and Signal
Processing
Angers, Loire Valley, France
ESEO
Paper deadline: Past: September
19, 2013
Call for papers.
3rd International Conference on Pattern Recognition Applications and
Methods
ICPRAM 2014
Angers, Loire Valley, France
ESEO
March 6-8, 2014
Paper deadline: Past: October 8,
2013 Extension
Call for papers.
March 6-8, 2014
Paper deadline: Past: November
19, 2013 Extension
Call for Position Papers.
Doctoral Consortium Paper
deadline: Past: December 10,
2013 Call for Participation.
March 6-8, 2014
Workshop on Image Processing
WIP 2014
March 11-14, 2014
Havana, Cuba
Part of International Conference on
Operations Research
Paper deadline: Past: January 10,
Call for papers. (PDF)
2014
ACM Multimedia Systems Conference
MMSys 2014
Singapore
Conference Venue
March 19-21, 2014
Paper deadline: Past: September
27, 2013
Call for papers.
March 19-21, 2014
Paper deadline: Past: November
11, 2013
Dataset Track.
March 19, 2014
NOSSDAV 2014: ACM Workshop
on Network and Operating
Paper deadline: Past: December
Systems Support for Digital Audio 13, 2013 Call for Papers
and Video
IEEE Winter Application and Computer Vision Conference
WACV 2014
March 24-26, 2014
Steamboat Springs, CO
Conference Venue
Paper deadline: Past: December
10, 2013 Second Round
Announcement.
Submissions. First Round: Paper
deadline: Past: September 2, 2013
International Conference on Computer Vision and Image Analysis
applications
ICCVIA 2014
March 25-27, 2014
Ras Al Khaimah, UAE
Conference Venue
Paper deadline: Past: January 21,
Call for papers.
2014
April 2014
Show this month on a map
ACM International Conference on Multimedia Retrieval
ICMR 2014
Glasgow, Scotland, UK
Conference Venue
April 1-5, 2014
Paper deadline: Past: December 2,
Call for papers.
2013
April 1-4, 2014
Doctoral Symposium
Deadline: Past: December 14, 2013
April 1, 2014
1st International Workshop on
Image Retrieval in Remote
Sensing (IR2S 2014)
Paper deadline: Soon: February 1,
2014 Call for Papers
April 1, 2014
International Workshop on
Environmental Multimedia
Retrieval 2014 (EMR 2014)
Paper deadline: Soon: February 1,
2014 Call for Papers
April 1 or 5, 2014
Workshop Proposals
Deadline: Past: November 15, 2013
Site Proposal Deadline: Past:
September 21, 2012
Call for Sites.
Southwest Symposium on Image Analysis and Interpretation
SSIAI 2014
April 6-8, 2014
San Diego, California, USA
Conference Venue
Paper deadline: Past: December
16, 2013
Call for papers.
EvoApplications 2014 track on Evolutionary Computation in Image
EvoIASP 2014 Analysis, Signal Processing and Pattern Recognition
April 23-25, 2014
Granada, Spain
Part of the EvoStar conference
Paper deadline: Past: November
11, 2013
Call for papers.
May 2014
Show this month on a map
The Fifth IEEE International Conference on Computational Photography
ICCP 2014
May 2-4, 2014
Santa Clara, CA, USA
Conference Venue
Paper deadline: Past: December
13, 2013
Call for papers.
11th Canadian Conference on Computer and Robot Vision
CRV 2014
May 7-9, 2014
Montreal, PQ, Canada
Conference Venue
Paper deadline: Soon: February
3, 2014
Call for papers.
Google Earth KMZ file for CRV Locations
ISPRS Symposium on Geospatial databases and location based
services
Geospatial 2014
May 14-16, 2014
Suzhou, China
Conference Venue
Paper deadline: Past: January 12,
Call for papers.
2014
Florida Artificial Intelligence Research Society Conference, FLAIRS 27
FLAIRS 2014
May 21-23, 2014
Pensacola Beach, Florida
Conference Venue
Paper deadline: Past: November
Call for papers.
18, 2013
5th International Conference on Geographic Object-Based Image
Analysis
GEOBIA 2014
May 21-23, 2014
Thessaloniki, Greece
Makedonia Conference Hotel
Paper deadline: Past: November
18, 2013
Call for papers.
16th The International Workshop on Combinatorial Image Analysis
IWCIA 2014
May 28-30, 2014
Brno, Czech Republic
Brno University of Technology
Paper deadline: Past: November
15, 2013
Call for papers.
Spring Conference on Computer Graphics
SCCG 2014
May 28-30, 2014
Smolenice Castle, Slovakia
Conference Venue
Paper deadline: March 2, 2014
Call for papers.
June 2014
Show this month on a map
22nd International conference on Computer Graphics, Visualization and
Computer Vision
WSCG 2014
June 2-5, 2014
Plzen (close to Prague), Czech
Republic
Conference Venue
Paper deadline: March 5, 2014
Call for papers.
2014 IEEE Intelligent Vehicles Symposium
IV 2014
Ypsilanti, Michigan, USA
Conference Venue
June 8-11, 2014
Paper deadline: Past: January 24,
Call for papers.
2014 Extension
IEEE Conference on Computer Vision and Pattern Recognition
CVPR 2014
June 17-19, 2014
Greater Columbus Convention
Center
Columbus, Ohio
Paper deadline: Past: November 1, Call for papers Additional
2013
Information. Call for Proposals.
Sponsored by IEEE-CS TC PAMI.
Google Earth KMZ file for CVPR Locations
12th International Workshop on Content-Based Multimedia Indexing
CBMI 2014
June 18-20, 2014
Klagenfurt, Austria
Alpen-Adria Universität Klagenfurt
Paper deadline: February 16, 2014 Call for papers.
Sixth International Conference on Image and Signal Processing
ICISP 2014
Cherbourg, Normandy, France
Conference Venue
June 30-July 2, 2014
Paper deadline: Soon: February
8, 2014
Call for papers.
June 30-July 2, 2014
Special Session: Color Imaging
and Applications
Paper deadline: Soon: February 8,
2014 Call for Papers
BMVA Computer Vision Summer School 2014
BMVA Vision
2014
June 30-July 4, 2014
Swansea University, UK
Conference Venue
Registration deadline: May 5, 2014 Call for participation.
July 2014
Show this month on a map
The 10th International Conference on Intelligent Environments
IE 2014
July 2-4, 2014
Shanghai, China
Conference Venue
Paper deadline: Soon: January
31, 2014
Call for papers.
Medical Image Understanding and Analysis
MIUA 2014
July 9-11, 2014
London, UK
Conference Venue
Paper deadline: March 17, 2014
Call for papers.
Vision for Language and Manipulation
Vision Language
London, UK
2014
5 Southampton Street
July 11, 2014
Call for papers.
Paper deadline: April 3, 2014
International Computer Vision Summer School: From Fundamentals to
Applications
ICVSS 2014
July 13-19, 2014
Punta Sampieri, Sicily, Italy
Hotel Village Baia Samuele
Enrollment deadline: March 31,
2014.
Call for participation.
IEEE International Conference on Multimedia and Expo
ICME 2014
July 14-18, 2014
Chengdu, China
Conference Venue
Paper deadline: Past: December 3,
Call for papers.
2013 Full paper 6 days later
VIII Conf. on Articulated Motion and Deformable Objects
AMDO 2014
July 16-18, 2014
Palma de Mallorca, Spain
Universitat de les Illes Balears
Paper deadline: March 21, 2014
Call for papers.
Medical Imaging Summer School: Medical Imaging meets Computer
MISS 2014
July 28-August 1, 2014
Vision
Favignana, Sicily, Italy
Conference Venue
Application deadline: March 31,
2014
Call for Participation.
August 2014
Show this month on a map
SIGGRAPH 2014
SIGGRAPH 2014 Vancouver, BC
Conference Venue
August 10-14, 2014
Call for papers.
Paper deadline:
International Conference on Machine Vision and Machine Learning
MVML 2014
August 14-15, 2014
Prague, Czech Republic
Conference Venue
Paper deadline: March 15, 2014
Call for papers.
International Conference on Multimedia and Human-Computer
Interaction
MHCI 2014
August 14-15, 2014
Prague, Czech Republic
Conference Venue
Paper deadline: March 15, 2014
Call for papers.
Statistical+Structural and Syntactic Pattern Recognition Workshop
S+SSPR 2014 Stockholm, Sweden
August 20-22, 2014
Before ICPR
Site Proposal deadline: Past: June
Call for Proposals.
15, 2012
International Conference on Pattern Recognition
ICPR 2014
Stockholm, Sweden
Conference Venue
August 24-28, 2014
Paper deadline: Past: December
20, 2013
August 24, 2014
Visual observation and analysis of Paper deadline: May 1, 2014 Call
animal and insect behavior (VAIB) for Papers
August 24, 2014
AMMDS: Activity Monitoring by
multiple distributed sensing
Call for papers.
Paper deadline: April 14, 2014
Google Earth KMZ file for ICPR Locations
11th International Conference on Signal Processing and Multimedia
Applications
SIGMAP 2014
August 28-30, 2014
Vienna, Austria
Part of ICETE
Paper deadline: April 15, 2014
Call for papers.
September 2014
Show this month on a map
British Machine Vision Conference
BMVC 2014
September 1-5, 2014
Nottingham, England
University of Nottingham
Paper deadline: May 2, 2014
Call for papers.
The 22nd European Signal Processing Conference
EUSIPCO 2014 Lisbon, Portugal
September 1-5, 2014
Conference Venue
Paper deadline: February 17, 2014 Call for papers.
German Conference on Pattern Recognition
GCPR 2014
September 2-5, 2014
Münster, Germany
Formerly the DAGM symposium.
Paper deadline: May 11, 2014
Call for papers. (PDF)
European Conference on Computer Vision
ECCV 2014
Zurich, Switzerland
September 6-12, 2014 Paper deadline: March 7, 2014
September 5-7, 2014
ISPRS Technical Commission III
Symposium Photogrammetric
Computer Vision (PCV 2014)
Conference Venue
Call for papers.
Paper deadline: April 13, 2014 Call
for papers.
Conference and Labs of the Evaluation Forum
CLEF 2014
Information School, University of
Sheffield
Sheffield, UK
September 15-18, 2014 Paper deadline:
Call for papers.
September 15-18, 2014 Image CLEF
Result deadline: May 1, 2014
Variable
September 15-18, 2014 Life CLEF
Result deadline: May 1, 2014
Variable Information.
Artificial Intelligence Applications and Innovations
AIAI 2014
Rhodes, Greece
September 19-22, 2014 Paper deadline: April 22, 2014
Conference Venue
Call for papers.
October 2014
Show this month on a map
15th International Computer Graphics Conference
VIEW 2014
October 14-17, 2014
Turin, Italy
TorinoIncontra
Paper deadline: July 31, 2014
Call for papers.
IEEE International Conference on Image Processing
ICIP 2014
October 27-30, 2014
Paris, France
CNIT La Defense
Paper deadline: Soon: January
31, 2014
Call for papers.
Google Earth KMZ file for ICIP Locations
November 2014
Show this month on a map
12th Asian Conference on Computer Vision
ACCV 2014
November 1-5, 2014
Singapore
Conference Venue
Paper deadline: June 15, 2014
Call for papers.
Iberomerican Conference on Pattern Recognition
CIARP 2014
November 2-5, 2014
Port Vallarta, Guadalajara, Jalisco,
Conference Venue
México
Paper deadline: May 2, 2014
Call for papers.
December 2014
Show this month on a map
Neural Information Processing Systems
NIPS 2014
December 1-4, 2014
Lake Tahoe, NV
Conference Venue
Paper deadline:
Call for papers.
Sponsored by NIPS Foundation.
2015
March 2015
Show this month on a map
5th Computational Color Imaging Workshop
CCIW 2015
March 24-25, 2015
Saint-Etienne, France
Conference Venue
Paper deadline:
Call for papers.
June 2015
Show this month on a map
IEEE Conference on Computer Vision and Pattern Recognition
CVPR 2015
Boston, MA
Conference Venue
June 7-12, 2015
Paper deadline:
Call for papers.
June 7-12, 2015
Proposal deadline: Past: May 15,
2012
Call for Proposals. Boston Proposal
Sponsored by IEEE-CS TC PAMI.
Google Earth KMZ file for CVPR Locations
September 2015
Show this month on a map
International Conference on Computer Analysis of Images and Patterns
CAIP 2015
September 2-4, 2015
Valetta, Malta
Mediterranean Conference Centre
Paper deadline:
Call for papers.
December 2015
Show this month on a map
International Conference on Comuter Vision
ICCV 2015
Santiago, Chile
Conference Venue
December 7-13, 2015 Paper deadline:
Call for papers.
Google Earth KMZ file for ICCV Locations
2016
June 2016
Show this month on a map
IEEE Conference on Computer Vision and Pattern Recognition
CVPR 2016
June 2016
Seattle, WA
Conference Venue
Proposal deadline: Past: May 15,
2013
Proposals. Call for Proposals.
Sponsored by IEEE-CS TC PAMI.
Google Earth KMZ file for CVPR Locations
2017
International Conference on Comuter Vision
ICCV 2017
Date TBD
Venice
Conference Venue
Paper deadline:
Call for papers.
Google Earth KMZ file for ICCV Locations
Other Calls for Papers
CVIU: Image Understanding for Real-world Distributed Video Networks
Special Issue Publication: Q4, 2014
Paper deadline: Past: January 20,
2014 Extension
Call for papers (PDF).
IEEE Sensor Journal: Distributed Smart Sensing for Mobile Vision
Special Issue Publication: Q4 2014
Paper deadline: March 1, 2014
Call for papers.
Conference Information Archives
Archives
Copyright © © 2013
The Computer vision group at USC has descriptions of a number
of research projects.
Maintained by Keith Price, bibupdate@visionbib.com.
To list an appropriate conference: email a text version of the summary
information. A text version of the call for papers is also useful.
Search the complete conference listings. List near-term deadlines. Browse
summary listing.
Home Page.Index for This Year (Past meetings)
This page has lots of images; a text-only page is also available.
See Vision 1's commercial resource listing for applications groups.

A. B. Kogan Research Institute for Neurocybernetics - Lab for Neural Network
Modeling in Vision Research

ANU Biorobotic Vision group

ARTEMIS Project Unit Advanced research on multidimensional imaging systems :
3D/2D vision medical imaging telecommunications and multimedia
 Aachen University of Technology - Department of Technical Computer Science Specializes in human
media technology and in knowledge based and trainable systems (computer vision and computational
intelligence)
 Aachen University of Technology - Language Processing and Pattern Recognition (Computer Science
VI) The object recognition group specializes in statistical image object recognition.
 Aalborg University - Computer Vision & Media Technology Laboratory

Academia Sinica - Laboratories of Intelligent Systems

Adelaide University - Computer Vision Lab Primarily researching (1) structure from
motion and related geometric problems in computer vision, and (2) video surveillance and analysis. (See
publications.)

Amerinex Applied Imaging Inc.
 Aristotle University of Thessaloniki Computer Vision and Image Processing group

Auckland U, Tamaki Campus, Computer Vision Unit at Tamaki
 Belarusian Academy of Sciences - Laboratory of Image Processing and Recognition

Berlin Technical University Computer Vision group
 Bilkent University - RETINA Vision and Learning Group

Boston University Image and Video Computing Research group
 Brown Universtity - SHAPE Lab Shape representation, 3D object and scene reconstructions, Object
recognition, Computer vision for Architecture, Archaeology, CAD, and beyond.
 Computational Interaction and Robotics Lab Our group is interested in understanding the problems
that involve dynamic, spatial interaction at the intersection of vision, robotics, and human-computer
interaction.

CREATIS - Center for Research and Applications in Image and Signal Processing
 CRIN / INRIA Lorraine Image Synthesis and Analysis group
 CSSIP - Visual Processing Research Group

Computer Vision and Imaging Group Model-based human tracking, robust methods and
medical image understanding.
 Caltech Vision group

Cambridge University Speech, Vision and Robotics group
 Cankaya University - Pattern Recognition and Image Processing Lab

Cardiff University - Vision and Geometry Research Group Specialises in machine
vision, automated inspection, 3d vision, geometric computing, medical imaging, and computer graphics

Carnegie Mellon Digital Mapping Lab
 Carnegie Mellon University / University of Karlsruhe - Interactive Systems Lab Specializes in
multimodal human computer interaction, real-time face tracking, eye/gaze tracking, lipreading

Carnegie Mellon Vision and Autonomous Systems Center
 Center for Applied Vision and Imaging Sciences
 Center for Biological and Computational Learning at MIT
 Technical University of Cluj-Napoca Image Processing and Pattern Recognition Group Our main
activities are research and teaching in the fields of image processing, pattern recognition, computer
vision, hardware design for image acquisition and processing.
 Colorado State University Computer Vision group


Columbia University - Robotics Group Group
Columbia University Automated Vision Environment, CAVE
 Computer Vision Group at HCMUNS
 IT University of Copenhagen - Image Group The Image Analysis (IA) group performs research within
the foundation of image and shape analysis and primarily medical image analysis applications.
 Cornell Vision Group
 Curtin University AI and Computer Vision
 Cyclops Project - Research on Computer Vision Applications in Medicine The Cyclops Project is a
German/Brazilian project aimed at the development of an intelligent envoironment for the support of
diagnopsis-oriented medical image analysis tasks. The Project is supported by the German-Brazilian
Cooperation Programme on Information Technology.


Czech Technical University, Prague - Center for Machine Perception
DKFZ Heidelberg - Medical and Biological Informatics
 DLR - The Institute of Robotics and Mechatronics - Vision Group
 Projects include video OCR, handwriting recognition, face analysis

Delft University Pattern Recognition Group
 Artificial Vision, Robotics and Intelligent Systems Group The main scope of the group is to perform
and promote research in application problems that rise in the science of electrical and computer
engineering, as well as in the production engineering one. Such applications are robotics, image
processing, analysis and understanding, digital arts, database image retrieval, quality control, visual
surveillance and intelligent sensory networks. The tools that the group uses to expand the front of the
science and the corresponding research areas of interest are: Artificial Vision (including Machine Vision,
Cognitive Vision and Robot Vision) Intelligent Systems (such as Fuzzy Systems and Artificial Neural
Network) Sensor Data Fusion Pattern Recognition
 Dublin City University - Machine Vision Group Specializes in real time hand gesture recognition,
pattern analysis and recognition, and vision-based systems.
 Dundee University - Computer Vision Group Research topics include human tracking, gesture
recognition, monitoring for independent living, vision-based interfaces, medical image analysis and
medical imaging

ECRC User Interaction and Visualisation Group

IBM Research - Exploratory Computer Vision Group

EPFL - Computer Vision Laboratory We focus on modeling people and their motion
from images and video sequences.
 ETH Zürich Image Science group
 ETH Zurich - Perceptual Computing and Computer Vision Group
 EUTIST Integrated Machine Vision Cluster EUTIST-IMV is a European Commission supported initiative
to help companies to innovate and improve their businesses by using machine vision technology. The
website introduces the on-going projects and gives practical examples of machine vision solutions for
different industries and applications.

Environmental Research Institute of Michigan (ERIM)
 Federal University of Santa Catarina - Intelligent Industrial Systems Group (Sistemas Industriais
Inteligentes) Home-page of the Intelligent Industrial Systems group of the Federal University of Santa
Catarina (UFSC), Brazil.
 Center for Applied Vision and Imaging Sciences The Center for Applied Vision and Imaging Sciences
(CAVIS) at Florida State University is dedicated to research and education in computer vision, pattern
recognition and applications.

Foundation for Research and Technology - Hellas, Computer Vision and Robotics Lab

Fraunhofer Institute for Computer Graphics Multimedia Systems and Image
Processing dept
 French Ministry of Defense (DGA) - Geography, Imagery, and Perception Group The activities
concerned are the processing and the exploitation of information, available mainly but not restrictively
to images (visible, infrared, synthetic aperture radar), applied to robotics, image-based intelligence and
geomatics.
 GE Research - Computer Vision Group Computer vision at GE includes basic and applied research in
surveillance, aerial and broadcast video understanding; medical imaging; industrial inspection; and
general image analysis.

GET Computer Vision lab

Georgia Tech - Computational Perception Laboratory The Computational Perception
Laboratory (CPL) was developed to explore and develop the next generation of intelligent machines,
interfaces, and environments that can perceive, recognize, anticipate, and interact with humans.

Graz University of Technology - Computer Graphics and Vision Group Focal points are
Machine Vision, Image Analysis and Computer Graphics Applications are in areas such as machine vision
in industry and medicine, 3D-modelling of objects, buildings and urban ensembles, and environmental
remote sensing
 Halmstad University - Signal Analysis Group Basic research specialization: Orientation analysis,
Symmetries and Tensors, local structure, texture and motion segmentation. Applied research
specialization: Multimodal person authentication, face recognition, content based image retrieval,
object recognition
 Hamburg University Cognitive Systems group (KOGS) (most info in German)
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Hamburg University IMA Research Group
Harvard Robotics Lab
Heart Institute of São Paulo Division of Informatics R&D group

Hebrew University Computer Vision Lab
 Heriot-Watt University - Image Systems Engineering Laboratory
 Heriot-Watt University Vision and Image Processing

Honeywell - Video-Based Surveillance and Security Group This objective of
the group is to invent, design, and integrate innovative video-based technologies into a distributed
architecture to enhance the efficiency and capabilities of surveillance and security systems.

Hungarian Academy of Sciences - Image and Pattern Analysis
Group Textures and patterns: fundamental structural features Motion: feature-based tracking Image
and video databases: retrieval Industrial inspection: shape defect detection
 Hunter College of CUNY - Computer Vision Laboratory

and Graphics Laboratory
Hunter College, City University of New York - Computer Vision
 IDIAP Computer Vision Group The computer vision group studies problems in machine visual
perception, such as media annotation, people detection and human gesture tracking and recognition.

IEN Galileo Ferraris Computer Vision lab
 IIT Delhi - Vision and Graphics Laboratory

INRIA - Perception and Integration for Smart Spaces

INRIA - Surgery, Informatics & Robotics (Chirurgie, Informatique &
Robotique) research in the key areas of robotics surgery: modeling of deformable organs, planning and
simulation of robotics procedures and safe & real-time integration.
 INRIA Rhone-Alpes - Models for Computer Vision

INRIA Vision Home Page, Sophia Antipolis center, INRIA Home Page
 INSA Lyon - Reconnaissance de Formes et Vision Pattern Recognition and Vision
 Indian Institute of Science - Computer Vision Lab

Industrial Research Ltd Machine Vision
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Institute for Industrial Automation - Artificial Perception Group specializing in
sensor integration and active perception
 Institute of Automation - National Laboratory of Pattern Recognition
 Institute of Clinical Physiology CNR - Computer Vision Group Development of new mathematical
operators for the purpose of both understanding biological vision and developing real-time imageprocessing systems.
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Institute of Systems and Robotics - Computer Vision Laboratory
Instituto Superior Tecnico - VisLab - Computer Vision Lab
 UCHIMURA & HU Laboratory
 Human and Computer Vision Laboratory

Israel Computer Vision research alliance

Istituto Trentino di Cultura - Technologies of Vision Mission of TeV is to
develop innovative techniques devoted to applicative topics, which currently include: Content based
indexing of documents, images and videos, surveillance and biometic person identification.
 JPL Machine Vision and Tracking Sensors group
 KTH - Computational Vision and Active Perception Lab at KTH (Sweden's Royal Institute of
Technology)

Medical Image Computing Specializes in 2-D and 3-D medical image acquisition,
manipulation, display, analysis, transmission, and archiving.
 Katholieke University Leuven VISICS

Khoral Research, Inc creators of Khoros
 Kiel Cognitive Systems group
 King's College London - Image Processing Group Image processing and analysis
 Korea University - Center for Artificial Vision Research Specializes in biologically motivated computer
vision
 Korean Research Groups in Visual Information Processing

Laboratory of Motion Analysis and Virtual Reality Specialized in analysis and synthesis of
human motion through image processing.

Laval University Computer Vision and Systems Lab
 Lawrence Berkeley Lab Imaging and Distributed Computing
 Lawrence Berkeley National Laboratory - Imaging and Collaborative Computing Group Algorithms
and software tools for scientific imaging applications.
 Le2i - Laboratory of Electronics, Computer Science and Image Processing Webpage of the Le2i, a
french research lab on computer vision and image processing
 Leeds University - Computer Vision Group Our specialities are in the areas of tracking and behaviour
modelling, medical imaging, the use of colour in image coding and compression, and OMR and
handwriting recognition.
 Lehigh University - Image Processing and Pattern Analysis Lab Mammogram Analysis, Image
Database Retrieval, Gesture Recognition and Industrial Inspection.
 Lehigh University - Vision And Software Technology Laboratory Research includes 3D vision, realtime tracking, omni-directional processing, remote reality and teleoperation, super-resolution imaging,
medical-imaging, multi-res imaging/algorithms, image-oriented user interface issues, IUE, CORBA, and
DCE.
 Leiden University Imaging and Multimedia group
 Linköping University Division of Computer Vision
 Luebeck University of Medicine - Institute for Signal Processing Medical and industial image
processing, pattern recognition and classification bio-signal processing,
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Lund University - Mathematical Imaging Group Computer vision, image analysis
and tomography from a mathematical perspective.
 MIT - CS & AI Lab Vision Research
 MIT - Perceptual Science Group
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MIT-Media Lab Vision and Modelling Group
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McGill Centre for Intelligent Machines
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Michigan State Pattern Recognition and Image Processing lab

Microsoft Research
 Middle East Technical University - Image Processing and Pattern Recognition Group

Laboratory
Middle East Technical University - Image Processing and Pattern Recognition

University of Minnesota Artifical
Intelligence, Robotics and Vision Laboratory Specializes in human activity monitoring, intelligent
transportation systems, and distributed robotics.

NEC Computer Vision and Image Processing
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NRC (National Research Council of Canada) - Computational Video Group Stereo
processing from off-the-shelf cameras, camera path computation (as seen on the logo), recognition and
tracking from video, reconstruction from multiple cameras, ubiquitous video
 Nanyang Technological University - Vision and Control Research Program - vision-guided automation

National Research Council of Canada - Visual Information Technology Group 3-D laser
range sensing; geometric image processing; object and environment modeling of shape and reflectance;
applications in computer graphics, manufacturing, robotics.
 National Technical University of Athens Computer Vision, Speech Communication and Signal
Processing Group Multiscale image analysis, enhancement, feature extraction and object detection with
algebraic, geometric and statistical methods. Analysis and modeling of shape, texture, color, and
motion.
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National University of Singapore - Computer Vision Research Group
 New York University - Vision Research concentration on human vision
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Niigata University - Yamamoto-Hoshino Laboratory
North Carolina State University - Image Analysis Laboratory
Northwestern University - Image and Video Processing Laboratory

Norwegian University of Science and Technology - Signal Processing Group
 Notre Dame Vision-Based Robotics using Estimation
 Ohio State University - Computer Vision Laboratory Specializes in human activity analysis

Ohio State University - Signal Analysis and Machine Perception Laboratory Perceptual
organization, 3D vision, stereo.

Ohio State University - Vision and Learning Group
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Oxford University - Robotics Research Group Active Vision, Projective Geometry,
Medical Image Analysis
 Oxford University - Visual Geometry Group Specializes in visual reconstruction from uncalibrated
image sequences.
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Oxford University Active Vision lab, and Robotics Research group
 Parma University Computer Vision
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Penn State Computer Vision
 Politecnico di Milano - Image and Sound Processing Group
 Politecnico di Torino - Computer Graphic and Vision Group

Technology
Postech Computer Vision Group - Pohang University of Science and
 Precision Digital Images

Purdue Robot Vision lab
 Purdue University - Video and Image Processing Laboratory (VIPER)
 Queen Mary and Westfield College Vision group
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Queen's University of Belfast - Centre for Image and Vision Systems
 RADIUS - Research and Development for Image Understanding Systems
 Real-Time Vision Group at Fraunhofer IIS Real-Time Face Detection, Face Biometrics, Camera
Tracking and 3D Reconstruction, Mobile Robot Vision
 Rensselaer Polytechnic Institute (RPI) Computer Science Vision Group
 Ritsumeikan University - Computer Vision Laboratory
 Rovira i Virgili University - Intelligent Robotics and Computer Vision Group Research Lines:
Disassembly Planning, Multiagent Systems, Planning and Scheduling, Image Analysis and Processing, 3D
Modeling, Real-Time Systems, Computer Architectures
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Rutgers University Image Understanding Lab
SRI International 's Perception Program at its AI Center
 SUNY at Stony Brook - Computer Vision Lab
 Statistical Visual Computing Laboratory research in both fundamental and applied problems in
computer vision, image processing, machine learning, and multimedia.
 Sarnoff - Vision Technology Group
 Seoul National University - 3D Visual Information Procesing Lab Computer vision research, especially
in range image processing, object recognition.
 Sheffield Hallam University - Microsystems & Machine Vision Laboratory

Sheffield Hallam University - Microsystems and Machine Vision Laboratory Microrobotic
systems and real-time computer vision (Kindly remove previous link with regards to
http://vision.eng.shu.ac.uk on the list)
 Sheffield Hallam University Computer Vision, Pattern Recognition and Artificial Intelligence
Group Research on 3D image acquisition, surface reconstruction, and image registration and fusion
 Simon Fraser University Computational Vision lab
 Smith-Kettlewell Eye Research Institute
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Stanford University - National Biocomputation Center Focus is on 3D imaging and
visualization technologies for biomedical applications.
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Stanford Vision Lab
Stanford Vision and Imaging Science and Technology

Swiss Federal Institute of Technology - Computer Vision Group Computer
vision group performs research in the fields of medical image analysis and visualization, shape modeling
and visualization, and remote sensing.

Swiss Federal Institute of Technology - Vision@IPM Group Specializes in visionbased quality control of industrial processes and automated, model-based image analysis.

Swiss Group for AI and Cognitive Science
 TU Munich - Image Understanding Group
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TU Munich - Robot Vision Group vision for autonomous robots
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Technical University Denmark - Dept of Mathematical Modeling Section for Image
Analysis Development and use of methods and theory in practical applications: Biomedical Imaging,
Industrial Vision, Material Science, and Remote Sensing.
 Technical University of Lisbon - Image Group
 Technical University of Vienna Pattern Recognition and Image Processing
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Technion Center for Intelligent Systems Technion -- Israel Institute of Technology
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Technion-Israel Institute of Technology - Vision Research and Image Science
Laboratory Main fields of interest: Pattern recognition, Analysis of color images, Clinical applications of
imaging systems, Image segmentation, Biological and computational vision systems, Computer graphics,
Robot vision research, Virtual reality and stereoscopic vision.
 Photogrammetry Division - University of Tehran - Iran we work on vision systems in intelligent
vehicles, vision metrology systems, softcopy workstations for mapping, Feature extraction in LIDAR or
ALS data and we are interested in anythings which related to photogrammetry and comuter vision.
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Tel Aviv University - Computer Vision
 Telecom Paris - Image Processing and Understanding Group
 Trinity College Computer Vision and Robotics Group
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UBC Lab for Computational Intelligence
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Research lab
 University of Houston's Visual Computing Lab
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USC Computer Vision
UC San Diego Computer Vision and Robotics
 Universidad de Las Palmas de Gran Canaria - Mathematical Analysis of Images We are interested in
applications of Partial Differential Equations to Computer Vision, Image Denoising and Enhancement,
Optic Flow , Dense Disparity Map, 3-D Geometry Reconstruction, Medical Imaging, Mutiscale Analysis,
etc..
 University College London - Laboratory of computational vision Computational, theoretical, and
psychophysical Studies of biological and artificial visual systems
 University Jaume I - Computer Vision Group
 University Jaume I - Computer Vision Group Research on several areas of image analysis and pattern
recognition.
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University Jaume I - REGEO Geometric Reconstruction Group Studying the problem of
automatically generating 3D models from 2D sketches.
 University of Aberdeen - Parallel and Image Processing Research Group
 University of Algarve Vision Laboratory

Systems Group
University of Amsterdam - Intelligent Autonomous
 University of Amsterdam - Intelligent Sensory Information Systems The central research themes of
ISIS are image databases and computer vision, particularly where the two themes meet. We do strategic
and fundamental research regularly in a multi-disciplinary and applied setting
 University of Antwerp - Vision Lab
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University of Autonònoma de Barcelona Computer Vision Center
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University of Bern Research Group on Computer Vision and AI

University of Bielefeld - Applied Computer Science
Group research in the area of pattern analysis, computer vision, and speech understanding and
applications to bioinformatics and natural sciences
 University of Bielfeld - Neuroinformatics Group
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University of of Birmingham - Digital Systems and Vision Processing Group basic research in
motion analaysis, unsupervised segmentation, model-based image interpretation, reconfigurable and
novel architectures for image interpretation, speech analysis, speech synthesis and its application in
medicine, industrial inspection and education.
 University of Bologna - Biometric Systems Lab The main research effort of the Biometric Systems Lab
is devoted to develop efficient automatic systems for classification, identification and recognition of
human characteristics, such as hand shape, fingerprint and face. Our ongoing contacts with industrial
partners ensure that our research results will be tested in real applications.
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University of Bologna- Vision Mathematics Group Our team works at the use of topology and
geometry in computer vision and robotic applications. We are mainly interested in the use of Size
Functions and Size Theory for shape comparison.
 University of Bonn CSD III Computer Vision and Pattern Recognition group
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University of Bonn Institute for Photogrammetry
University of Bremen Institute for Neurophysics
 University of Brighton - Applied Image Processing Resource Unit
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University of Bristol Image Processing and Computer Vision Group
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University of California Berkeley Computer Vision group
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University of California Irvine Computer Vision lab
 University of California Irvine Vision Research
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University of California San Diego Visual Computing lab
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University of California Santa Barbara - Four Eyes Lab Research in "imaging, interaction, and
innovative interfaces" (four I's) - primary focus on computer vision, HCI, and augmented reality.
 University of California Santa Barbara - Image Processing & Vision Research Labs
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Vision Lab
University of California, Los Angeles -
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Systems Laboratory (VISLab)
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University of California, Riverside Visualization & Intelligent
University of Cape Town Image Processing lab
University of Central Florida Computer Vision lab
University of Chicago Vision and Robotics group
 University of Cologne Pattern Recognition group

University of Copenhagen - Image Research Group
 University of Costa Rica - Image Processing and Computer Vision Research Laboratory (IPCVLAB) Our current research projects include image segmentation, pose, shape, color, motion and mimic
estimation of real objects for robotics, on-line inspection, in-situ microscopy and video compression.
 University of Edinburgh - Machine Vision Unit
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University of Erlangen - Computer Vision, Image Processing and Analysis

University of Essex - Vision Group face recognition, autonomous vehicle
navigation, motion and occlusion, edge finding
 University of Exeter - Pattern Analysis and Neural Networks Group Pattern Analysis and Neural
Networks
 University of Florida Center for Computer Vision and Visualization
 University of Freiburg - Chair of Pattern Recognition and Image Processing
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University of Geneva Vision Group
University of Genova - LIRA-Lab Laboratory for integrated advanced robotics
 University of Georgia - Visual and Parallel Computing Laboratory The goal of the VPCL is to advance
the state of the art in the theory and applications of Visual Computing and Parallel Computing. Current
projects deal with machine vision for inspection and production planning, image analysis of DNA
microarrays, pattern recognition problems in DNA analysis, analysis of motion in video sequences and
applications of parallel computing to the above problems.
 University of Glasgow - 3D-MATIC Research Laboratory By combining the science of
'photogrammetry' with digital camera technology, it is now possible to capture 3D models of people,
animals and objects that are both metrically accurate and photo-realistic in appearance. Ongoing
research within the Partnership is also exploring 3D data extraction from still images and movie
sequences and the extension of the imaging technology to capture images in real time.

University of Granada - Computer Vision Group Specializes in image representational models,
distortion measures, target distinctness and image compression

University of Granada Digital Image Analysis group

University of Guelph - Robot Vision Group of Intelligent Systems Lab We are interested in
exploring real-time dynamic visual processes (e.g., tracking, optical flow, binocular vision) cast in a
particle filter framework. We also explore using these visual processes for autonomous robot control in
conjunction with markovian planning techniques for various applications such as elderly or disabled aids,
search and rescue robotics, intelligent automobiles,...

University of Hannover - Institute for Photogrammetry and GeoInformation specialises in
photogrammetry, remote sensing, and aerial image analysis, in connection with geographic information
systems
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University of Hannover Institut für Theoretische Nachrichtentechnik und
Informationsverarbeitung (TNT)
 University of Hawaii at Manoa - Image Sequence Processing Group Specializes in the application of
vision models (particularly local frequency representations and segmentation-based models) to image
and image sequence processing and computer vision.

University of Heidelberg - Digital Image Processing Group Scientific Applications
 University of Illinois Chicago - Computer Vision and Robotics Laboratory
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University of Illinois Urbana-Champaign Robotics and Computer Vision
University of Iowa Division of Physiologic Imaging
 University of Jena Digital Image Processing group

University of Koblenz Image Recognition lab

University of Ljubljana - Computer Vision Laboratory

University of Louisville - Computer Vision and Image Processing Lab Computer vision and
Medical Imaging research

University of Maryland Computer Vision Lab
 University of Massachusetts Amherst - Computer Vision Laboratory

University of Massachusetts Amherst - Laboratory for Perceptual Robotics

University of Melbourne Computer Vision and Machine Intelligence lab

University of Messina - Vision Lab Still image segmentation and real-time image analysis

University of Miami - Underwater Vision and Imaging Laboratory
 University of Modena and Reggio Emilia - Image Processing Laboratory
 University of Modena and Reggio Emilia - Imagelab
 University of Montreal - Computer Vision & Geometric Modeling Lab

University of Nevada - Computer Vision Laboratory
 University of North Carolina at Charlotte - Vision Group We are currently working on areas such as
Gesture recognition, Vision based tracking for VR, and Skin Detection studies
 University of Nottingham - Image Processing and Interpretation Research Group The Image
Processing & Interpretation (IPI) Research Group addresses basic issues in image processing and
analysis, machine vision and artificial intelligence. The group combines theoretical and applied research,
working within forcing domains provided by real problems and applications.
 University of Otago - Computer Vision Research Group

University of Ottawa - Video, Image, Vision and Audio Research Group Categories
include: Computer Vision, Image Processing, Video and Audio Processing and Coding.

University of Oulu Machine Vision and Media Processing Group

University of Paraná - Computer Vision and Image Processing Group Our
current research focuses on range image segmentation, 3D modeling from range images, medical
images processing, visualization and content-based image retrieval.

University of Pavia - Vision
Lab Specializes in visual attention mechanisms; includes human-computer interfaces
 University of Pennsylvania - Vision Analysis and Simulation Technologies Laboratory We do research
in computer vision (shape and motion estimation), computer graphics and medical image analysis
 University of Pennsylvania GRASP lab
 University of Pennsylvania Medical Image Processing Group

University of Pisa - Industrial Vision Lab Artificial vision applications to manufacturing
processes and product quality control.
 University of Plymouth - Robotic Intelligence Laboratory The lab focuses on problems related to the
design of intelligent domestic and helper robots. These include artificial vision for object recognition and
vision for spatial navigation, actions planning and sequencing, and natural language instruction
dialogues with the user.
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University of Politecnica Madrid - Computer Vision Group Automatic visual automation in
manufacturing three-dimesional vision visual information management systems
 University of Reading - Computational Vision Group

University of Rochester - Vision and Robotics research Lab
 University of Rochester Center for Electronic Imaging Systems
 University of São Paulo - Creative Vision Group Specializes in person recognition using video
sequences

São Carlos

University of São Paulo Cybernetic Vision Research group at the Instituto de Fisica de
University of Saskatchewan Computer Vision

University of South Florida Image Analysis Research Group
 University of Southampton - Image, Speech, and Intelligent Systems
 University of Southamton Image, Speech and Intelligent Systems Group (ISIS)
 University of Southern California - Visual Processing Laboratory
 University of Surrey Vision, Speech, and Signal Processing Group
 University of Sussex COGS Vision Research
 University of São Paulo - Image Computing Group, Medical Physics
 University of Technology, Sydney - Computer Vision and Cluster Computing Lab Focusing on clusterbased computer vision within the Spiral Architecture.

Systems lab
University of Tennessee, Knoxville - Imaging, Robotics, and Intelligent

University of Toronto - Computational Vision Group

University of Twente - Laboratory for Measurement and Instrumentation
 University of Udine - Machine Vision Lab
 University of Ulster Computer Vision and Image Processing Research group
 University of Utah - Center for Scientific Computing and Imaging
 University of Utah Robotics and Computer Vision

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University of Verona - Vision, Image Processing, and Sound Laboratory
University of Virginia Computer Vision Research (CS)
 University of Washington - Information Processing Lab
 University of Washington Image Computing Systems Lab
 University of West Florida Image Analysis/Robotics Research Laboratory
 University of Western Australia Robotics and Vision research group

University of Wisconsin Computer Vision group
 University of York Computer Vision and Pattern Recognition
 University of of California, San Diego - Computer Vision & Robotics Research Lab
 University of of Plymouth - Centre for Intelligent Systems
 University of of Texas - Laboratory for Vision Systems
 University of of Zagreb Image Processing Group
 University of the Balearic Islands - Computer Graphics and Vision Group

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University of the West of England - Machine Vision Group Specialize in surface inspection
Utrecht University - Image Science Institute Focus is on medical imaging
 Vanderbilt University Center for Intelligent Systems

Vienna University of Technology - Pattern Recognition and Image Processing
Group Object recognition, 3D Computer Vision, Graph theory in CV, AI methods in CV
 Computer Vision Group at Vietnam National University of HCMC - Univ of Natural Sciences Our
research are concentrated on Object detection, recognition, tracking, Human activity recognition and
tracking.
 Vincent Torre Lab at SISSA
 Virage, Inc.
 Computer Vision Group at Virginia Tech Applied research in computer vision and pattern recognition.

Vision Systems Laboratory, RINCE/DCU: Centre for Applied Imaging and Vision
Systems Research group
 Washington University St. Louis - CVIA Lab specializing in medical computer vision
 Weizmann Institute of Science - Computer Vision Lab
 Wright State University Intelligent Systems Lab


Wright-Patterson Model Based Vision Lab
Yale School of Medicine Image Processing and Analysis Group
 Vision Lab at York University Research in the Vision Lab at York University concentrates on theoretical
and applied aspects of computer vision, with a particular emphasis on stereo and motion analysis.

York University - Center For Vision Research carries out research into sensory and motor
processes, perception, and computer vision.
 York University Vision, Graphics and Robotics
 eyeTap Personal Imaging Lab The ePI Lab is a is a computer vision research and development lab
focused on the area of personal imaging, mediated reality and wearable computers.

Statistical Learning & Image Processing Genova University Research Unit Our research focuses
on: (1) the study of mathematically sound methods for solving classification problems (2) the
development of techniques for extracting visual information from images.

Laboratory for
imagery, vision, and artificial intelligence a team of multidisplinary reserachers on the field of artificial
vision, pattern recognition, image processing, learning algorithms, genetic computing, artificial
intelligence, and perception
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