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Reformulating the Costeira-Kanade algorithm as a pure mathematical theorem independent of the Tomasi-Kanade factorization, we present a robust segmentation algorithm by incorporating such techniques as dimension correction, model selection using the geometric AIC, and least-median fitting. Doing numerical simulations, we demonstrate that oar algorithm dramatically outperforms existing methods. It does not involve any parameters which need to be adjusted empirically
Digital Object Identifier: 10.1109/ICCV.2001.937679
Published with permission from the copyright holder. This is the institute's copy, as published in Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on, 7-14 July 2001, Volume: 2, Pages 586-591.
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