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Motion segmentation by multistage affine classification

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4 Author(s)
G. D. Borshukov ; Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA ; G. Bozdagi ; Y. Altunbasak ; A. M. Tekalp

We present a multistage affine motion segmentation method that combines the benefits of the dominant motion and block-based affine modeling approaches. In particular, we propose two key modifications to a recent motion segmentation algorithm developed by Wang and Adelson (1994). 1) The adaptive k-means clustering step is replaced by a merging step, whereby the affine parameters of a block which has the smallest representation error, rather than the respective cluster center, is used to represent each layer; and 2) we implement it in multiple stages, where pixels belonging to a single motion model are labeled at each stage. Performance improvement due to the proposed modifications is demonstrated on real video frames

Published in:

IEEE Transactions on Image Processing  (Volume:6 ,  Issue: 11 )