Abstract：To solve the complexity and variability of video background for moving object detection in video, a new algorithm was proposed based on the canonical correlation tree weighted belief propagation. The image was separated into some blocks with the same size to establish loop model. The treereweighted algorithm was used to decompose the loop into spanning tree, and the detection of moving targets on the loop model was achieved. The canonical correlation analysis was used to solve the canonical correlation coefficients between adjacent subblocks, and then the two subblocks with the maximum value were linked to form new loop. The iteration of the tree weighted belief propagation was adopted to update the information, and the moving targets were detected. The experimental results show that the run time of the proposed algorithm is 9.8 s, and the similarity with the original image is over 95％. The proposed algorithm can detect and separate the moving target accurately with reliable speed, and it is suitable for real time detection of moving targets.
2015, Vol. 36 
