Anomaly detection in surveillance videos based on H265 and deep learning

Abstract

Shopping malls, banks, hospitals, markets, educational institutions, smart cities, and roadways are all places where video surveillance systems (VSS) are commonly used to improve public safety. The correctness and speed with which video anomalies are identified are usually the primary focus of security applications. Recently, many surveillance cameras have been installed at various locations around the world for public safety purposes. Massive volumes of video data are continuously generated by these cameras