Motion segmentation by subspace separation and model selection
Kanatani, K.
Dept. of Inf. Technol., Okayama Univ.;
This paper appears in: Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on
Publication Date: 2001
Volume: 2,
On page(s): 586-591 vol.2
Meeting Date: 07/07/2001 - 07/14/2001
Location: Vancouver, BC, Canada
ISBN: 0-7695-1143-0
References Cited: 12
INSPEC Accession Number: 7024331
Digital Object Identifier: 10.1109/ICCV.2001.937679
Current Version Published: 2002-08-07
Abstract
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
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