title: Large disparity motion layer extraction via topological clustering.
abstract: In this paper, we present a robust and efficient approach to extract motion layers from a pair of images with large disparity motion. First, motion models are established as: 1) initial SIFT matches are obtained and grouped into a set of clusters using our developed topological clustering algorithm; 2) for each cluster with no less than three matches, an affine transformation is estimated with least-square solution as tentative motion model; and 3) the tentative motion models are refined and the invalid models are pruned. Then, with the obtained motion models, a graph cuts based layer assignment algorithm is employed to segment the scene into several motion layers. Experimental results demonstrate that our method can successfully segment scenes containing objects with large interframe motion or even with significant interframe scale and pose changes. Furthermore, compared with the previous method invented by Wills and its modified version, our method is much faster and more robust.
authors.affiliation: Institute for Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology,Wuhan, China 430074. wytiprai@gmail.com
authors.forename: Yongtao
authors.initials: Y
authors.lastname: Wang
authors.forename: Junbin
authors.initials: J
authors.lastname: Gong
authors.forename: Dazhi
authors.initials: D
authors.lastname: Zhang
authors.forename: Chenqiang
authors.initials: C
authors.lastname: Gao
authors.forename: Jinwen
authors.initials: J
authors.lastname: Tian
authors.forename: Huanqiang
authors.initials: H
authors.lastname: Zeng