Research on video synopsis optimization method based on Two-stage abnormal behavior recognition
Fudan Wang, Zhixiang Zhu, Chenwu Wang, Pei Wang, Lei Zhang, Pengyuan Mu · 2023
Video synopsis techniques shift the moving target in the time axis to achieve the purpose of displaying as much effective information as possible in the shortest possible time, usually the abnormal behavior in the video contains more effective information, and most of the existing video synopsis methods do not consider the processing of abnormal behavior. To solve this problem, this paper proposes a video synopsis method based on two-stage abnormal behavior recognition. First, the abnormal frames containing abnormal behaviors in surveillance video are detected using a spatiotemporal autoencoder method, and then an improved R(2+1)D network model is used to identify the abnormal targets and abnormal behavior classes in the abnormal frames of surveillance video. Finally, the abnormal priority concentration loss term is added to the video synopsis optimization objective loss function to make the abnormal targets appear more preferentially and centrally in the generated synopsis video by the multi-objective optimization algorithm. Through a large number of experimental results, the method proposed in this article not only prioritizes the appearance of abnormal targets in the synopsis video, but also accurately observes the specific abnormal behavior of abnormal targets.