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Symmetric Sub-pixel Stereo Matching

  • Richard Szeliski
  • Daniel Scharstein
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2351)

Abstract

Two central issues in stereo algorithm design are the matching criterion and the underlying smoothness assumptions. In this paper we propose a new stereo 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.

Keywords

Stereo Match Match Cost Stereo Algorithm Occlude Area 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 2002

Authors and Affiliations

  • Richard Szeliski
    • 1
  • Daniel Scharstein
    • 2
  1. 1.Microsoft ResearchRedmondUSA
  2. 2.Middlebury CollegeMiddleburyUSA

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