Mixed-motion Segmentation Using Helmholtz Decomposition

Abstract

Motion estimation and segmentation poses challenges in dynamic scenarios where multiple motions are mixed up and interdependent. However, existing approaches in 2D motion field usually require the mixed motions to be independent. Algorithms incorporating 3D information have proven to be superior to purely 2D approaches in many studies. Inspired by this idea, we propose a new algorithm for evolving 3D potential surfaces using Helmholtz decomposition to represent 2D motion field. Meanwhile, a surface segmentation scheme is introduced to put different motions onto different layers, so that those interdependent motions can be separated and recovered efficiently. Unlike other approaches, our method does not require the prior knowledge of the motion model. The performance is demonstrated using real data under various complex scenarios.