@inproceedings{hstorr2002dense,
author = {H.S. Torr, Philip and Criminisi, Antonio},
title = {Dense Stereo Using Pivoted Dynamic Programming},
booktitle = {British Machine Vision Conference},
year = {2002},
month = {January},
abstract = {Abstract This paper describes an improvement to the dynamic programming approach for dense stereo. Traditionally dense stereo algorithms proceed independently for each pair of epipolar lines, and then a further step is used to smooth the estimated disparities between the epipolar lines. This typically results in a streaky disparity map along depth discontinuities. In order to overcome this problem the information from corner and edge matching algorithms are exploited. Indeed we present a unified dynamic programming/statistical framework that allows the incorporation of any partial knowledge about disparities, such as matched features and known surfaces within the scene. The result is a fully automatic dense stereo system with a faster run time and greater accuracy than the standard dynamic programming method.},
url = {http://approjects.co.za/?big=en-us/research/publication/dense-stereo-using-pivoted-dynamic-programming-5/},
}