PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Global Stereo Reconstruction under Second-Order Smoothness Priors
Oliver Woodford, Philip Torr, Ian Reid and Andrew Fitzgibbon
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) Volume 31, Number 12, pp. 2115-2128, 2009. ISSN 0162-8828

Abstract

Second-order priors on the smoothness of 3D surfaces are a better model of typical scenes than first-order priors. However, stereo reconstruction using global inference algorithms, such as graph cuts, has not been able to incorporate second-order priors because the triple cliques needed to express them yield intractable (nonsubmodular) optimization problems. This paper shows that inference with triple cliques can be effectively performed. Our optimization strategy is a development of recent extensions to \alpha--expansion, based on the “ QPBO” algorithm. The strategy is to repeatedly merge proposal depth maps using a novel extension of QPBO. Proposal depth maps can come from any source, for example, frontoparallel planes as in \alpha-expansion, or indeed any existing stereo algorithm, with arbitrary parameter settings.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Learning/Statistics & Optimisation
ID Code:6206
Deposited By:Karteek Alahari
Deposited On:08 March 2010