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Conference Papers Year : 2006

Disparity Map Estimation Using A Total Variation Bound

Abstract

This paper describes a new variational method for estimating disparity from stereo images. The stereo matching problem is formulated as a convex programming problem in which an objective function is minimized under various constraints modelling prior knowledge and observed information. The algorithm proposed to solve this problem has a block-iterative structure which allows a wide range of constraints to be easily incorporated, possibly taking advantage of parallel computing architectures. In this work, we use a Total Variation bound as a regularization constraint, which is shown to be well-suited to disparity maps. Experimental results for standard data sets are presented to illustrate the capabilities of the proposed disparity estimation technique.
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Dates and versions

inria-00001255 , version 1 (14-04-2006)

Identifiers

  • HAL Id : inria-00001255 , version 1

Cite

Wided Miled, Jean-Christophe Pesquet, Michel Null Parent. Disparity Map Estimation Using A Total Variation Bound. Third Canadian Conference on Computer and Robot Vision, Jun 2006, Quebec. ⟨inria-00001255⟩
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