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Fast Adaptive Graph-Cuts Based Stereo Matching

  • Michel Sarkis
  • Nikolas Dörfler
  • Klaus Diepold
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4678)

Abstract

Stereo vision is one of the central research problems in computer vision. The most difficult and important issue in this area is the stereo matching process. One technique that performs this process is the Graph-Cuts based algorithm and which provides accurate results . Nevertheless, this approach is too slow to use due to the redundant computations that it invokes. In this work, an Adaptive Graph-Cuts based algorithm is implemented. The key issue is to subdivide the image into several regions using quadtrees and then define a global energy function that adapts itself for each of these subregions. Results show that the proposed algorithm is 3 times faster than the other Graph-Cuts algorithm while keeping the same quality of the results.

Keywords

Cost Function Stereo Image Coarse Level Stereo Match Stereo Match Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Michel Sarkis
    • 1
  • Nikolas Dörfler
    • 1
  • Klaus Diepold
    • 1
  1. 1.Institute for Data Processing (LDV), Technische Universität München (TUM), MunichGermany

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