Probabilistic occlusion boundary detection on spatio-temporal lattices

In this paper, we present an algorithm for occlusion boundary detection. The main contribution is a probabilistic detection framework defined on spatio-temporal lattices, which enables joint analysis of image frames. For this purpose, we introduce two complementary cost functions for creating the spatio-temporal lattice and for performing global inference of the occlusion boundaries, respectively. In addition, a novel combination of low-level occlusion features is discriminatively learnt in the detection framework. Simulations on the CMU Motion Dataset provide ample evidence that proposed algorithm outperforms the leading existing methods.

• Type: Journal
• Year: 2009
• Where: ICCV
• Authors: Mehmet Emre Sargin, Luca Bertelli, Bangalore S. Manjunath, Kenneth Rose
• Keywords: Computer Vision, Detection Framework, ICCV 2009, Occlusion Boundary Detection, Spatio-temporal Lattice