Conceptual and Experimental
Vision
Introduction
R.Bajcsy, S.Sastry and A.Yang
Fall 2006
Introduction and plan for the course
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We plan to follow the text :An Invitation to 3-D Vision by
Yi Ma, Stefano Soatto,Jana Kosecka and S.S.Sastry.
Plus some additional papers on real time, Active Vision.
Approximately every two weeks there will be a problem
set and programming homework assignment
There will no midterm and final, but projects instead.
Students are expected to participate in the class.
The proposed Syllabus
• Week 1: Introduction
• Week 2: Image formation : geometry, optics , Radiometry
and error analysis
• Week 3: Image primitives and correspondence
• Week 4: Review of basic algebra and geometry
• Week 5 :Epipolar geometry
• Week 6: Camera calibration
• Week 7: Structure from motion
• Week 8: Optimization
Syllabus cont.,
• Week 9: Real Time Vision
• Week 10: Visual feedback
• Week 11: Active Vision
• Week 12: Introduction to GPCA: Iterative methods
• Week 13: Introduction to GPCA:Algebraic Methods
• Week 14: Estimation and Segmentation of Hybrid
Models, and Applications
• Week 15:Projects
Our expectation
• Through this course, students should acquire the ability
to study computer vision through rigorous mathematical
frameworks.
• By the end of the course, students should be familiar
with the history of computer vision, the start-of-the-art
performance of current vision systems, and important
open problems in the literature.
• Experimentally, students should be able to setup a
stereo camera system, evaluate its characteristics,
calibrate it, and reconstruct motions of single and
multiple objects.
What is Vision?
• From the 3-D world to 2-D images: image formation
(physics).
• Domain of artistic reproduction (synthesis): painting,
graphics.
• From 2-D images to the 3-D world: image analysis and
reconstruction (mathematical modeling, inference).
• Domain of vision: biological (eye and brain)
computational
Topics from a vision conf.: CVPR06
CVPR 2006 cont.
CVPR 2006 cont.
CVPR 2006 cont.
What we will cover
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Geometry
Stereo and 3D reconstruction
Matching and Registration
Segmentation
Real time considerations
Visual feedback and control
Error analysis of the sensor system
What we will not cover
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Recognition
Learning
Tracking and video analysis
Low level analysis an graphics and Image Synthesis
Our Brain
Our eye vs. Camera
Multiple views
Camera’s multiple views
Illusions
Illusions for Prof. Ramachandran
• http://psy.ucsd.edu/chip/video/Mot_Capt_LQ.rm
What painters knew
Perspective Imaging and other
monocular cues
Image Analysis
3-D Modeling and Rendering
3-D Modeling and Rendering
Image Mosaicing and panoramic views
3-D reconstruction
3-D data acquisition and reconstruction
Geometry and Photometry
Compare recovered shape and laser
scanned object
Data Acquisition and integration of
Indian Baskets
Real Time Virtual Object Insertion
UAV at Berkeley
Vision based driving
Tele-Immersive environment for
Communication