Sparse Occlusion Detection with Optical Flow

Abstract We tackle the problem of detecting occluded regions in a video stream. Under assumptions of Lambertian reflection and static illumination, the task can be posed as a variational optimization problem, and its solution approximated using convex minimization. We describe efficient numerical schemes that reach the global optimum of the relaxed cost functional, for any number of independently moving objects, and any number of occlusion layers. We test the proposed algorithm on benchmark datasets, expanded to enable evaluation of occlusion detection performance, in addition to optical flow. Keywords Occlusion detection · Optical flow · Convex optimization · Sparse optimization · Nesterov’s algorithm · Split-Bregman method

• Type: Journal
• Year: 2012
• Where: IJCV
• Authors: Alper Ayvaci, Michalis Raptis, Stefano Soatto
• Keywords: Computer Networks, Convex Optimization, IJCV 2012, Occlusion Detection, Optimization Problem