title: Motion segmentation by multistage affine classification.
abstract: 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.
authors.forename: G D
authors.initials: GD
authors.lastname: Borshukov
authors.forename: G
authors.initials: G
authors.lastname: Bozdagi
authors.forename: Y
authors.initials: Y
authors.lastname: Altunbasak
authors.forename: A M
authors.initials: AM
authors.lastname: Tekalp