Motion Segmentation with Occlusions on the Superpixel Graph

Motion Segmentation with Occlusions on the Superpixel Graph

Conference

Abstract

​​We present a motion segmentation algorithm that partitions the image plane into disjoint regions based on their parametric motion. It relies on a finer partitioning of the image domain into regions of uniform photometric properties, with motion segments made of unions of such “superpixels.” We exploit recent advances in combinatorial graph optimization that yield computationally efficient estimates. The energy functional is built on a superpixel graph, and is iteratively minimized by computing a parametric motion model in closed-form, followed by a graph cut of the superpixel adjacency graph. It generalizes naturally to multilabel partitions that can handle multiple motions.

Details

PUBLISHED IN
International Conference on Computer Vision Workshops: Dynamical Vision (ICCVW)
PUBLICATION DATE
15 okt. 2009
AUTHORS
A. Ayvaci, S. Soatto