Video synopsis algorithm based on two-stage target tubes grouping

Abstract

Video synopsis generates a concentrated video that can be browsed quickly. With the increase of condensation ratio, more pseudo collisions between target tubes will occur. To solve this problem, this paper proposed a video synopsis algorithm based on two-stage target tubes grouping. In the first stage, using the hypergraph to analyze the collision relationship between target tubes, and the target tubes are grouped according to the hyper-edges. In the second stage, a clustering algorithm based on equal distance nearest neighbor sampling is proposed to group the target tubes. Then, selecting target tubes according to the selection principle of quantity priority between groups and length priority within groups (QPB-LPG) . Finally, these target tubes are rearranged to generate concentrated videos with smaller pseudo collisions. The experimental results show that this algorithm can significantly reduce the pseudo collision between target tubes without reducing the frame condensation ratio and frame compact rate compared with existing video concentration algorithms, and the feasibility of the method is fully verified.