Efficient video object segmentation using adaptive background registration and edge-based change detection techniques

The work presents an automatic and efficient video object segmentation algorithm. Moving object extraction is carried out by adaptive background model and edge-based change detection techniques. The background is updated by use of pixel history and a moving object mask. Connected component analysis and morphological filtering are employed to obtain an accurate VOP (video object plane). Finally, a novel object tracking window scheme is applied to improve the processing speed. Experimental results for three different types of MPEG-4 video sequences are shown to demonstrate the effectiveness of the proposed algorithm.