Video Sequence Segmentation Method, Based On The Movement Of The Edge Information

Following the standard of MPEG-4 and the increasing availability of video in digital form, there is growing demand for methods of automatically analyzing video. In the object-based standard of MPEG-4, in order to support content-based functions, each frame of video should be represented in terms of video object planes (VOP).The first stage is the segmentation of the frames into regions representing different real world objects which have different motion. Exactly, the ideal segmentation should provide a clear partition of objects and the relative depth ordering of each object.Motion segmentation is the necessary stage of most video analysis implements, and it divides frames into different regions according different motion so that those motion objects can be abstracted. This paper presents an improved theoretical framework for motion segmentation based on the motion of tracked edges. Firstly, abstract these edges of objects by Canny algorithm, then tracking edges along normal direction to get normal motion. Secondly, applying Expectation-Maximization algorithm to the two motions alternately to calculate the motions and the responsibility of every edges, repeat the step until it is convergent. Finally segment the sequence into regions by region growing algorithm, and get the final result by region labeling. The practical result has proved the validity of the improved motion tracking and region labeling method.