Chin-Shyurng Fahn1, Chang-Yi Kao2,*, Meng-Luen Wu3, Hao-En Chueh4
Computer Systems Science and Engineering, Vol.42, No.2, pp. 451-463, 2022, DOI:10.32604/csse.2022.022368
Abstract With the evolution of video surveillance systems, the requirement of video storage grows rapidly; in addition, safe guards and forensic officers spend a great deal of time observing surveillance videos to find abnormal events. As most of the scene in the surveillance video are redundant and contains no information needs attention, we propose a video condensation method to summarize the abnormal events in the video by rearranging the moving trajectory and sort them by the degree of anomaly. Our goal is to improve the condensation rate to reduce more storage size, and increase the accuracy in abnormal detection. As the… More >
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