Statistical Inference for Automatic Video Object Segmentation

In the new MPEG-4video coding standard,the automatic video object segmentation plays a key role in supporting object-oriented coding and enabling content-based functionalities.Background subtraction is one of the basic methods of automatic video object segmentation.But the great variety of environmental illumination conditions often makes it hard to work.A statistical inference based background subtraction method is presented.A statistical background model is first setup,then the hypothesis testing is applied to the following frames to segment the video objects.HSV color model is also used and its color components are analyzed and treated separately so that the proposed algorithm can adapt to different environmental illumination conditions.Experimental results show this algorithm can automatically segment video objects accurately in various illuminating environments.