説明
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.
収録刊行物
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- Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001
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Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001 2 586-591, 2002-11-13
IEEE Comput. Soc
