Skip to Main content Skip to Navigation
Conference papers

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.
Document type :
Conference papers
Complete list of metadata

Cited literature [21 references]  Display  Hide  Download
Contributor : Wided Miled Connect in order to contact the contributor
Submitted on : Friday, April 14, 2006 - 4:41:22 PM
Last modification on : Thursday, January 20, 2022 - 5:29:47 PM
Long-term archiving on: : Saturday, April 3, 2010 - 11:11:59 PM


  • HAL Id : inria-00001255, version 1


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



Les métriques sont temporairement indisponibles