Identification of Trajectory Anomalies on Video Surveillance Systems

Recently, CCTV surveillance applications have remarkably developed for public welfare. However, the investigation of different techniques online implementation is always significantly restricted. Numerous implementations propose detecting irregularities moving objects in videotape. Performance fuzzy trajectory's anomaly one most robust detection procedures. In this paper, authors a implemented trajectory anomalies technique with help some parameters such as velocity, path deviation, and size objects. The critical aspect framework compact set highly descriptive features extracted from novel cell structure that helps us define support regions coarse-to-fine fashion. This paper also illustrates small outline techniques. exhibit outcome experiments on Queen Mary University London junction dataset (QMUL).