Abstract:

Most of the current segmentation algorithms in compressed domain are often time-consuming and have incomplete segmentation for moving objects. In this paper,based on convexhull we propose a novel fast segmentation algorithm for object tracking in compressed domain. This algorithm mainly utilizes information of the motion vector field in bits stream to do segmentation.Firstly,an iteratively backward projection scheme is proposed in normalization to obtain an accumulated motion vector filed.Then the spatiotemporal filter (STF) algorithm is used to preprocess the motion vector field to obtain the stable MV field.The filled MV field is subsequently searched for building a convex hull and filling the region.Finally,the segmentation is accomplished after optimizing and forming a mask.The proposed method focuses on fast obtaining the whole moving object and a better segmentation accuracy,and the experimental results show that it can work well even when motion vector is severely lacking,and is better than the traditional methods.

Key words: compressed domain;fast segmentation;motion vector;spatio-temporal filter;convex hull