Geodesic Adaptive Support Weight Approach For Local Stereo Matching

A. Hosni, M. Bleyer, M. Gelautz, C. Rhemann:
"Geodesic Adaptive Support Weight Approach For Local Stereo Matching";
Vortrag: Computer Vision Winter Workshop 2010, Nove Hrady; 03.02.2010 - 05.02.2010; in:"Proceedings of the 15th Computer Vision Winter Workshop", Czech Society for Cybernetics and Informatics, (Czech Pattern Recognition Society group), Prague (2010), ISBN: 978-80-254-6499-1; S. 60 - 65.

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Abstract:


Local stereo matching has recently experienced large
progress by the introduction of new support aggregation
schemes. These approaches estimate a pixel´s support region
via color segmentation. Our contribution lies in an improved
method for accomplishing this segmentation. Inside a square
support window, we compute the geodesic distance from all
pixels to the window´s center pixel. Pixels of low geodesic
distance are given high support weights and therefore large
influence in the matching process. In contrast to previous
work, we enforce connectivity by using the geodesic distance
transform. For obtaining a high support weight, a pixel must
have a path to the center point along which the color does not
change significantly. This connectivity property leads to improved
segmentation results and consequently to improved
disparity maps. The success of our geodesic approach is
demonstrated on the Middlebury images. According to the
Middlebury benchmark, the proposed algorithm is the top
performer among local stereo methods at the current stateof-
the-art.