Abstract: Video segmentation is a hot issue in the field of image processing.Based on traditional segmentation algorithms,a new unsupervised video segmentation algorithm was proposed.This algorithm represents the moving foreground with superpixel algorithm,defines the join weight of superpixels as the possibility from the same object,and calculates the join weight with static features from current frame associated with the relevance feature between frames.In order to optimize the search of relevance match between superpixels from different frames,the algorithm introduces superpixel color feature constraint and movement constraint.The experiment contains two aspects,and the algorithm ensures higher recall rate and stable precision rate in the simple scenario and completes single person segmentation from the crowd in the complex scenes.Large numbers of experiments show that the proposed algorithm can realize video image segmentation,and effectively solve the problem of over-segmentation.

Key words: Video segmentation,Superpixel,Motion constraint,Over segmentation