A layered stereo algorithm using image segmentation and global visibility constraints

Abstract

We propose a new stereo algorithm which uses colour segmentation to allow the handling of large untextured regions and precise localization of depth boundaries. Each segment is modelled as a plane. Robustness of the depth representation is achieved by the use of a layered model. Layers are extracted by mean-shift-based clustering of depth planes. For layer assignment a global cost function is defined. The quality of the disparity map is measured by warping the reference image to the second view and comparing it with the real image. Z-buffering enforces visibility and allows the explicit detection of occlusions. An efficient greedy algorithm searches for a local minimum of the cost function. Layer extraction and assignment are alternately applied. Results obtained for benchmark and self-recorded images indicate that the proposed algorithm can compete with the state-of-the-art.

Reference

M. Bleyer, M. Gelautz: "A layered stereo algorithm using image segmentation and global visibility constraints"; Talk: IEEE International Conference on Image Processing, Singapore; 10-24-2004 - 10-27-2004.

BibTeX

@unpublished{TUW-138853, author = {Bleyer, Michael and Gelautz, Margrit}, title = {A layered stereo algorithm using image segmentation and global visibility constraints}, year = {2004}, note = {talk: IEEE International Conference on Image Processing, Singapore; 2004-10-24 -- 2004-10-27} } Click into the text area and press Ctrl+A/Ctrl+C or ⌘+A/⌘+C to copy the BibTeX into your clipboard… or download the BibTeX.