Title
Stereo Matching with Color-Weighted Correlation, Hierarchical Belief Propagation, and Occlusion Handling
Abstract
In this paper, we formulate a stereo matching algorithm with careful handling of disparity, discontinuity and occlusion. The algorithm works with a global matching stereo model based on an energy-minimization framework. The global energy contains two terms, the data term and the smoothness term. The data term is first approximated by a color-weighted correlation, then refined in occluded and low-texture areas in a {\it{repeated}} application of a hierarchical loopy belief propagation algorithm. The experimental results are evaluated on the Middlebury data sets, showing that our algorithm is the {\it{top}} performer among all the algorithms listed there.
Year
DOI
Venue
2009
10.1109/TPAMI.2008.99
Pattern Analysis and Machine Intelligence, IEEE Transactions
Keywords
Field
DocType
energy-minimization framework,stereo matching algorithm,color-weighted correlation,occlusion handling,careful handling,global energy,middlebury data set,stereo matching,global matching stereo model,algorithm work,hierarchical belief propagation,data term,smoothness term,visualization,cost function,loopy belief propagation,energy minimization,stereo vision,computer vision,pixel,belief propagation
Computer vision,Pattern recognition,Visualization,Stereopsis,Computer science,Discontinuity (linguistics),Correlation,Minification,Artificial intelligence,Pixel,Smoothness,Belief propagation
Journal
Volume
Issue
ISSN
31
3
0162-8828
ISBN
Citations 
PageRank 
0-7695-2597-0
271
11.21
References 
Authors
23
5
Search Limit
100271
Name
Order
Citations
PageRank
Qingxiong Yang12586106.93
Liang Wang261324.55
Ruigang Yang33675226.03
Henrik Stewenius42777165.83
David Nistér52265118.02