A region-based randomized voting scheme for stereo matching

Abstract

This paper presents a region-based stereo matching algorithm which uses a new method to select the final disparity: a random process computes for each pixel different approximations of its disparity relying on a surface model with different image segmentations and each found disparity gets a vote. At last, the final disparity is selected by estimating the mode of a density function built from these votes. We also advise how to choose the different parameters. Finally, an evaluation shows that the proposed method is efficient even at sub-pixel accuracy and is competitive with the state of the art. © 2010 Springer-Verlag.