The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

This paper presents a stereo algorithm for obtaining disparity maps with explicitly detected occlusion. To produce smooth and detailed disparity maps, two assumptions that were originally proposed by Marr and Poggio are adopted: uniqueness and continuity. That is, the dis-parity maps have unique values and are continuous almost everywhere. A volumetric approach is taken to utilize these assumptions. A 3D array of match likelihood values is constructed with each value corresponding to a pixel in an image and a disparity relative to another image. An iterative algorithm updates the match likelihood values by diffusing support among neighboring values and inhibiting others. After the values have converged, the region of occlusion is explicitly detected.

To demonstrate the effectiveness of the algorithm we present the processing results from synthetic and real image pairs, with comparison to results by other methods. The resulting dispar-ity maps are smooth and detailed with occlusions detected. Disparity values in areas of repetitive texture are also found correctly.

Keywords

Stereo vision, occlusion detection, volumetric, 3-D vision

Notes

Sponsor: Advanced Research Projects Agency under the Department of the Army, Army Research Office

Grant ID: DAAH04-94-G-0006

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

Associated Project(s): Cooperative Stereo Vision

Text Reference

Charles Zitnick and Takeo Kanade, "A Volumetric Iterative Approach to Stereo Matching and Occlusion Detection," tech. report CMU-RI-TR-98-30, Robotics Institute, Carnegie Mellon University, December, 1998

BibTeX Reference

@techreport{Zitnick_1998_503,
   author = "Charles Zitnick and Takeo Kanade",
   title = "A Volumetric Iterative Approach to Stereo Matching and Occlusion Detection",
   booktitle = "",
   institution = "Robotics Institute",
   month = "December",
   year = "1998",
   number= "CMU-RI-TR-98-30",
   address= "Pittsburgh, PA",
}

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