Skip to Main Content
Motion-based image segmentation is one of the basic problems of image processing and computer vision, with numerous applications to object based image coding and computer vision. This paper describes a novel algorithm for motion-based figure-ground segmentation based on the minimization of a functional for maximum separation between the motions of figure and ground. The Euler-Lagrange descent equations corresponding the minimization of this functional are expressed as level set partial differential equations for a topology-free formulation and stable numerical implementation. These level set partial differential equations dictate the evolution of a surface whose zero level set at convergence is the desired figure ground segmentation. Preliminary results validate our proposed algorithm and demonstrate that accurate figure-ground segmentation based on motion alone and with no prior computation of motion is obtained.