Research Of The Abnormal Behavior Detection Technology Based On The Surveillance Video

The existing video surveillance systems mostly have the detection or do tracking of moving targets within the scene, but have further processing is relatively few. But in the life, the purpose of monitoring is to detect and analyze abnormal behavior of the abnormal events or persons in the scene. Intelligent video surveillance detection of abnormal behavior can not only timely discover of improper conduct and inform the staffs of timely treatment to prevent the wrongful acts, but also save a lot of storage space to avoid searching and obtaining evidence by amounts of staff after the wrongful act occurred.This article mainly concentrates on human behavior analysis in the video surveillance, and takes the detection of abnormal human behavior as the core content. In the first part, this article described the development status of video surveillance system in detail. In the second part, it detailed Introduced computer vision technology in home and abroad as well as in intelligent video analysis, followed by technology and the development of the field of video surveillance, video surveillance, common image processing technology, as well as video surveillance, abnormal behavior detection technology and methods discussion and Analysis.In order to solve the traditional algorithm being difficult to detect a human moving target in the case of dynamic scenes, this paper proposes a new human motion abnormal behavior detection method, the combination use of video surveillance in various sports reference volume. The article mainly analyze the human behavior in video sequences, the purpose is to detect the body’s abnormal behavior, including:the human body moving target detection, tracking and extraction, and abnormal behavior detection. The paper describes the concept of abnormal behavior detection, and the computing method of each parameter in video monitor reference amount to explore the relationship of abnormal behavior detection and classification techniques. Combined with the similarity of the abnormal behavior detection and classification, this paper puts forward the abnormal behavior test method based on video surveillance, and provides the calculation method of video monitor reference amount, which settles on the detection process. Besides, this article also analyzed the characteristics and advantages of the method.Finally, using the OpenCV’s open source project code, design a video surveillance anomaly detection system prototype for testing, and uses a modular processing, surveillance video in the background of the actual self-service banking features, performance and stability testing to achieve real-time analysis and processing of video surveillance. The tested result shows that, abnormal behavior detection algorithm based on the video monitor movement reference amount can meet the practical needs and achieve the desired effect.The innovation points of this paper are:Put forward the abnormal behavior detection method based on the video monitor movement reference amount, improve the original reference model, and introduce the concept of reference volume of the movement of video surveillance.Realize the abnormal behavior detection system prototype based on the video monitor movement reference amount under the background the self-service banking video, and make the abnormal behavior detection more accurate and effective.