Real-time global stereo matching using hierarchical belief propagation

Qingxiong Yang, Liang Wang, Ruigang Yang, Shengnan Wang, Miao Liao, David Nistér

Research output: Contribution to conferencePaperpeer-review

226 Scopus citations


In this paper, we present a belief propagation based global algorithm that generates high quality results while maintaining real-time performance. To our knowledge, it is the first BP based global method that runs at real-time speed. Our efficiency performance gains mainly from the parallelism of graphics hardware, which leads to a 45 times speedup compared to the CPU implementation. To qualify the accurancy of our approach, the experimental results are evaluated on the Middlebury data sets, showing that our approach is among the best (ranked first in the new evaluation system) for all real-time approaches. In addition, since the running time of general BP is linear to the number of iterations, adopting a large number of iterations is not feasible for practical applications. Hence a novel approach is proposed to adaptively update pixel cost. Unlike general BP methods, the running time of our proposed algorithm dramatically converges.

Original languageEnglish
Number of pages10
StatePublished - 2006
Event2006 17th British Machine Vision Conference, BMVC 2006 - Edinburgh, United Kingdom
Duration: Sep 4 2006Sep 7 2006


Conference2006 17th British Machine Vision Conference, BMVC 2006
Country/TerritoryUnited Kingdom

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition


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