Stereo matching with implicit detection of occlusions

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1407)


In this paper we introduce a new stereo matching algorithm, in which the matching of occluded areas is suppressed by a self-organizing process. In the first step the images are filtered by a set of oriented Gabor filters. A complex-valued correlation-based similarity measurement, which is applied to the responses of the Gabor filters, is used in the second step to initialize a self-organizing process. In this self-organizing network, which is described by coupled, non-linear evolution equations, the continuity and the uniqueness constraints are established. Occlusions are detected implicitly without a computationally intensive bidirectional matching strategy. Due to the special similarity measurement, dense disparity maps can be calculated with subpixel accuracy. Unlike phase-difference methods the disparity range is not limited to the modulation wavelength of the quadrature-filter. Therefore, there is no need for a hierachical coarse-to-fine control strategy in our approach.


Gabor Filter Stereo Match Disparity Estimation Occlude Region Occlude Area 
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 1998

Authors and Affiliations

  1. 1.Department of Electrical EngineeringUniversity of PaderbornPaderbornGermany

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