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Comparison of two proximal splitting algorithms for solving multilabel disparity estimation problems
KTH, School of Electrical Engineering (EES), Sound and Image Processing.
2012 (English)In: 2012 Proceedings Of The 20th European Signal Processing Conference (EUSIPCO), IEEE Computer Society, 2012, 1134-1138 p.Conference paper, Published paper (Refereed)
Abstract [en]

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.
Series
European Signal Processing Conference, ISSN 2219-5491
Keyword [en]
convex optimization, disparity estimation, segmentation, stereo vision, total variation
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-106636ISI: 000310623800228Scopus ID: 2-s2.0-84869821057ISBN: 978-146731068-0 (print)OAI: oai:DiVA.org:kth-106636DiVA: diva2:574042
Conference
20th European Signal Processing Conference, EUSIPCO 2012, 27 August 2012 through 31 August 2012, Bucharest
Note

QC 20121204

Available from: 2012-12-04 Created: 2012-12-04 Last updated: 2013-01-14Bibliographically approved

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CiteExportLink to record
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  • apa
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  • Other locale
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Output format
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  • asciidoc
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