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Symmetric Sub-Pixel Stereo Matching

Richard Szeliski and Daniel Scharstein


Two central issues in stereo algorithm design are the matching criterion and the underlying smoothness assumptions. In this paper we propose a newstereo algorithm with novel approaches to both issues. We start with a careful analysis of the properties of the continuous disparity space image (DSI), and derive a new matching cost based on the reconstructed image signals.We then use a symmetric matching process that employs visibility constraints to assign disparities to a large fraction of pixels with minimal smoothness assumptions. While the matching operates on integer disparities, sub-pixel information is maintained throughout the process. Global smoothness assumptions are delayed until a later stage in which disparities are assigned in textureless and occluded areas.We validate our approach with experimental results on stereo images with ground truth.


Publication typeInproceedings
Published inSeventh European Conference on Computer Vision (ECCV 2002)
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