York Urban Line Segment Database Information
About the York Urban Line Segment Database
The York Urban Line Segment Database is a compilation of 102 images (45 indoor, 57 outdoor) 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 calibrated Panasonic Lumix DMC-LC80 digital camera.
Each image in the database has been hand-labelled to identify the set of line segments satisfying the “Manhattan assumption” (Coughlan & Yuille 2003), i.e., the set of line segments that conform to the 3D orthogonal frame of the urban environment.
These hand-labelled data have been used to identify the three Manhattan vanishing points in each image and from these to identify the Euler angles relating the camera frame to the Manhattan frame of the scene.
The database provides the original images, camera calibration parameters, ground truth line segments, and estimated Manhattan frame relative to the camera for each image.
Further details can be found in the readme file, 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.
This database can be used to train and evaluate methods for automatically computing the Manhattan frame, as in Denis, Elder & Estrada (2008), and for many other purposes.
Please contact Patrick at email@example.com if you have any questions about the database.
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. European Conference on Computer Vision, 2 (5303), 197-210.
Denis P. (2008). Efficient Edge-Based Methods for Estimating Manhattan Frames in Urban Imagery. M.Sc. Thesis, York University, Canada.
Click on YorkUrbanDB_Readme to download the readme file.
Click on YorkUrbanDB to download the YorkUrbanDB public ground truth database.