Video Segmentation Using Global Motion Estimation and Compensation

Emerging multimedia applications demands content-based video processing. Video has to be segmented into objects for content-based processing. A number of video object segmentation algorithms have been proposed such as semiautomatic and automatic. Semiautomatic methods adds burden to users and also not suitable for some applications. Automatic segmentation systems are still a challenge, although they are required by many applications. The proposed work aims at contributing to develop a system to segment video objects automatically from the background given a sequence of video frames. The proposed work will identify and solve different problems in change detection like uncovered background, global motion of background, temporary poses. To improve the resulting change detection masks, a post-processing method will be used. This technique is used to fill open areas inside object regions with uniform intensity. To improve the boundary of segmentation masks, morphological operations will be used.