SHORT-TERM MOTION-BASED OBJECT SEGMENTATION

Motion-based segmentation approaches employ either long-term motion information, which is computationally demanding, or suffer from lack of accuracy when employing short-term information. We present an automatic motion-based object segmentation algorithm for video sequences with moving camera, employing short-term motion information solely. For every frame, two error frames are generated using motion compensation. They are combined and a thresholding segmentation algorithm is applied. Recent advances in the field of global motion estimation enable outlier elimination in the background area, and thus a more precise definition of the foreground is achieved. We propose a simple and effective error frame generation and consider spatial error localization. Thus, we achieve improved performance compared with a previously proposed short-term motion-based method and provide subjective as well as objective evaluation.