Comparison of two proximal splitting algorithms for solving multilabel disparity estimation problems
2012 (English)In: 2012 Proceedings Of The 20th European Signal Processing Conference (EUSIPCO), IEEE Computer Society, 2012, 1134-1138 p.Conference paper (Refereed)
Disparity estimation constitutes an active research area in stereo vision, and in recent years, global estimation methods aiming at minimizing an energy function over the whole image have gained a lot of attention. To overcome the difficulties raised by the nonconvexity of the minimized criterion, convex relaxations have been proposed by several authors. In this paper, the global energy function is made convex by quantizing the disparity map and converting it into a set of binary fields. It is shown that the problem can then be efficiently solved by parallel proximal splitting approaches. A primal algorithm and a primal-dual one are proposed and compared based on numerical tests.
Place, publisher, year, edition, pages
IEEE Computer Society, 2012. 1134-1138 p.
, European Signal Processing Conference, ISSN 2219-5491
convex optimization, disparity estimation, segmentation, stereo vision, total variation
Engineering and Technology
IdentifiersURN: urn:nbn:se:kth:diva-106636ISI: 000310623800228ScopusID: 2-s2.0-84869821057ISBN: 978-146731068-0OAI: oai:DiVA.org:kth-106636DiVA: diva2:574042
20th European Signal Processing Conference, EUSIPCO 2012, 27 August 2012 through 31 August 2012, Bucharest
QC 201212042012-12-042012-12-042013-01-14Bibliographically approved