Study on Segmentation and Global Motion Estimation in Object Tracking Based on Compressed Domain

Abstract

Object tracking is an interesting and needed procedure for many real time applications. But it is a challenging one, because of the presence of challenging sequences with abrupt motion occlusion, cluttered background and also the camera shake. In many video processing systems, the presence of moving objects limits the accuracy of Global Motion Estimation (GME). On the other hand, the inaccuracy of global motion parameter estimates affects the performance of motion segmentation. In the proposed method, we introduce a procedure for simultaneous object segmentation and GME from block-based motion vector (MV) field, motion vector is refined firstly by spatial and temporal correlation of motion and initial segmentation is produced by using the motion vector difference after global motion estimation.