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We address the problem of epipolar geometry using the motion of silhouettes.Such methods match epipolar lines or frontier points across views, which arethen used as the set of putative correspondences. We introduce an approach thatimproves by two orders of magnitude the performance over state-of-the-artmethods, by significantly reducing the number of outliers in the putativematching. We model the frontier points' correspondence problem as constrainedflow optimization, requiring small differences between their coordinates overconsecutive frames. Our approach is formulated as a Linear Integer Program andwe show that due to the nature of our problem, it can be solved efficiently inan iterative manner. Our method was validated on four standard datasetsproviding accurate calibrations across very different viewpoints.

Camera Calibration by Global Constraints on the Motion of Silhouettes