YorkUrbanDB - README
Introduction
The York Urban Database is a compilation of 102 images of urban
environments consisting mostly of scenes from the campus of York
University and downtown Toronto, Canada. The images are 640 x 480 in
size and have been taken with a Panasonic Lumix DMC-LC80 digital
camera. This public database is further broken down into 45 indoor and
57 outdoor scenes which conform to the "Manhattan Assumption", that is,
the overlying structure in the scene conforms to a rectangular 3-D grid
(right angle structure) (Coughlan and Yuille, 2001).
Further details can be found in the ECCV conference paper (Denis, Elder
& Estrada 2008), and in Patrick's MSc thesis. If you use this
database, please cite the ECCV conference paper.
References
Coughlan, J. M., & Yuille, A. L. (2003). Manhattan world: Orientation
and outlier detection by Bayesian inference. Neural Computation, 15
(5), 1063 - 1088.
Denis, P., Elder, J.H. & Estrada, F. (2008). Efficient Edge-Based
Methods for Estimating Manhattan Frames in Urban Imagery. Proc.
European Conference on Computer Vision (5303), 197-211.
Denis, P. (2008). Efficient Edge-Based Methods for Estimating Manhattan
Frames in Urban Imagery. M.Sc. Thesis, York University, Canada.
Organization
In the main path there are 3 files, Manhattan_Image_DB_Names.mat,
cameraParameters.mat and ECCV_TrainingAndTestImageNumbers.mat.
1. Manhattan_Image_DB_Names.mat
PURPOSE: Contains the MATLAB filenames of all the images in the
database.
CONTENT:
Manhattan_Image_DB_Names - [102,1] cell array.
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2. cameraParameters.mat
PURPOSE: Internal camera parameters used to compute the Manhattan frame
for each image. See the ECCV paper and Patrick’s MSc thesis for details
on the calibration methods.
CONTENT:
focal - [1]
focal length of camera (mm).
pixelSize - [1]
The estimated size of the sensor pixels, in mm.
pp – [1,2]
Principal point in pixel coordinates. The principal point is stored in
(x, y) coordinates where the origin (1, 1) is the TOP LEFT of the
image.
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3. ECCV_TrainingAndTestImageNumbers.mat
PURPOSE: This file lists the randomly-selected partition of images into
training and test sets used in Denis, Elder & Estrada, ECCV 2008. This
may be useful if you wish to compare new algorithms directly against
the results reported in this paper.
CONTENT:
trainingSetIndex – [51,1]
Image numbers used for training set
testSetIndex – [51,1]
Image numbers used for test set
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Information for each of the 102 images in the database is stored in a
separate folder. Each of these folders contains:
1.
2.
3.
4.
<imageName>.jpg
<ImageName>LinesAndVP.mat
<ImageName>GroundTruthVP_CamParams.mat
<ImageName>GroundTruthVP_Orthogonal_CamParams.mat
4. <imageName>.jpg
PURPOSE: The original 640x480 image.
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5. <ImageName>LinesAndVP.mat
PURPOSE: Holds the MATLAB data pertaining to the labeled line segments
and vanishing point association.
CONTENT:
vp_association - [n,1]
Vanishing point associated with each of the n line segments.
values are {1,2,3}. Convention used:
Possible
1 – First horizontal vanishing point
2 - Vertical vanishing point
3 - Second horizontal vanishing point
lines - [2n,2]
Each line segment is represented by its endpoints, stored as a 2x2
array [x1 y1; x2 y2]. These are concatenated vertically, so that the
kth line segment is accessed as lines(2*k-1:2*k,:).
finalImg Image with
especially
accurately
[480,640,3]
the line segments overlaid.
short ones, are not drawn
due to aliasing.
Please note that some lines,
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6. <ImageName>GroundTruthVP_CamParams.mat
PURPOSE: This file contains the vanishing point vectors independently
estimated in the Gauss Sphere and estimated standard error. Since they
were estimated independently, these vectors are not exactly orthogonal.
CONTENT:
vp - [3,3] matrix containing the three vanishing point unit vectors
stored in column format.
vp_std_error - [1,3] the standard error computed for each vector.
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7. <ImageName>GroundTruthVP_Orthogonal_CamParams.mat
PURPOSE: This file contains orthogonalized estimates of the vanishing
point vectors.
CONTENT:
vp_orthogonal - [3,3] matrix containing the three orthonormal vanishing
point vectors stored in column format.