This package contains a fast and accurate procedure which verifies
correspondences by means of pixel-wise cosegmentation. The
algorithm is described in: Jan Cech, Jiri Matas, Michal Perdoch;
Efficient Sequential Correspondence Selection by Cosegmentation;
In CVPR, 2008, and is also available from
http://cmp.felk.cvut.cz/~cechj

@InProceedings{Cech-CVPR-2008,
 author = {Jan {\v C}ech, Ji{\v r}{\' i} Matas, Michal Per{\v d}och},
 title = {Efficient Sequential Correspondence Selection by Cosegmentation},
 booktitle = {IEEE Computer Society Conference on Computer Vision and Pattern Recognition},
 year = 2008,
 month = {June},
 venue = {Anchorage, Alaska, USA},
 keywords = {correspondence, verification, dense stereo, growing, sequential decison, learning, SVM, wide-baseline stereo, image retrieval, SIFT, RANSAC},
 psurl = {<a href="ftp://cmp.felk.cvut.cz/pub/cmp/articles/cech/Cech-CVPR-2008.pdf">[PDF]</a> },
 ISBN = {978-1-4244-2243-2},
 publisher = {Omnipress},
 address =  {Madison, WI, USA},
}

Please refer to that article if you are publishing results based
on this toolbox.

Run test_scv to test functionality and learn how to run the main
module.

This is free toolbox for a non-commercial purpose. Commercial use
requires a licence. The software is distributed AS IS, WITHOUT ANY
IMPLIED OR EXPRESSED WARRANTY and WITHOUT ANY FURTHER SUPPORT for
the desired and/or other purpose.

(c) Jan Cech (cechj@cmp.felk.cvut.cz) FEE CTU Prague, Apr 30, 2009

Compiled for: Matlab V7 for 32-bit Linux, 64-bit Linux, 32-bit
Windows
