An automatic segmentation algorithm for moving objects in video sequences under multi-constraints

A new algorithm under multi-constraints for automatic segmentation of video moving objects is proposed. First, the temporal segmentation separates the initial areas including moving objects accurately from the background by continuous frame difference. Then, the spatial segmentation segments the initial areas into spatially consistent regions by the watershed algorithm based on a color gradient. Finally, regions are classified as foreground/background by maximizing the a posterior probability (MAP) of the MRF with spatial, temporal and adjacent constraints. Experimental results demonstrate that the algorithm is not sensitive to objects' irregular movement and illumination, and it can extract moving video objects accurately.