Abstract: In order to effectively extract temporal motion information of videos for robust and precise video copy detection,this paper proposes a novel video feature based on behavior patterns of keypoint trajectories.By the algorithm,first the keypoint trajectories are generated and modeled into behavior patterns.Then patterns are learned using bag-of-visual-word method as video features.Finally,similarity between features is used for video copy detection.Comparison experiments on benchmark video dataset(TRECVID)show that proposed algorithm achieves high detection precision.And this work demonstrates that the trajectory based feature has better robustness for various visual changes.