Moving Object Segmentation Using Level Set Method with Shape Prior, Color and Texture

Abstract

This paper presents a method for the combination of different feature cues in a level set based moving object segmentation framework. To distinguish object from background, motion detection is firstly adopted to locate object position and obtain coarse shape prior. Moreover, the color and texture feature descriptors that represent object contour are designed in this dissertation. Then the finer segmentation solution based on the color and texture difference between the object and background is proposed, which avoids the invalid feature components to hamper segmentation and improves the accuracy. Extensive experiments have been carried out on surveillance video sequences to validate the proposed method.