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Carnegie Mellon Robotics Institute

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Abstract

Presents a stereo algorithm for obtaining disparity maps with occlusion explicitly detected. To produce smooth and detailed disparity maps, two assumptions that were originally proposed by Marr and Poggio (1976, 1979) are adopted: uniqueness and continuity. That is, the disparity maps have a unique value per pixel and are continuous almost everywhere. These assumptions are enforced within a three-dimensional array of match values in disparity space. Each match value corresponds to a pixel in an image and a disparity relative to another image. An iterative algorithm updates the match values by diffusing support among neighboring values and inhibiting others along similar lines of sight. By applying the uniqueness assumption, occluded regions can be explicitly identified. To demonstrate the effectiveness of the algorithm, we present the processing results from synthetic and real image pairs, including ones with ground-truth values for quantitative comparison with other methods.

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Associated Project(s): Cooperative Stereo Vision

Text Reference

Charles Zitnick and Takeo Kanade, "A cooperative algorithm for stereo matching and occlusion detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No. 7, July, 2000, pp. 675 - 684.

BibTeX Reference

@article{Zitnick_2000_3528,
   author = "Charles Zitnick and Takeo Kanade",
   title = "A cooperative algorithm for stereo matching and occlusion detection",
   journal = "IEEE Transactions on Pattern Analysis and Machine Intelligence",
   pages = "675 - 684",
   month = "July",
   year = "2000",
   volume = "22",
   number = "7",
}

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