Design Of Video Surveillance System Research Articles

Human Behavior Recognition of Video Surveillance System Based on Neural Network

Video surveillance system is widely used in modern society. Human behavior recognition based on neural network uses computer vision and image processing technology to analyze and judge the behavior of different objects in surveillance video. In order to improve the recognition accuracy of human behavior, this paper makes an in-depth study on the design of video surveillance system and target tracking using the relevant algorithms of neural network. In this paper, the application of relevant neural network algorithms and the technology of character behavior recognition are analyzed by means of experimental method comparison and algorithm comparison. The experimental data shows that in the detection of abnormal behavior, the highest accuracy rate of human behavior recognition is 90% by using the improved hu invariant moment model.

Sound based alarming based video surveillance system design

Sound based alarming based video surveillance system design

A Chemical Embedded Video Monitoring System Based on Real-Time Video Compression MPEG4 Encoding

Among the digital monitoring system, MPEG4 encoding compression technology and embedded technologies are widely used, chemical embedded MPEG4 video surveillance system has a broad market prospect and highly advanced technology. In this paper, the MPEG coding standards and on the basis of analysis of the characteristics, given a set of MPEG4 video surveillance system design, and implementation are integrated MPEG4 exposition, after the actual chemical application shows that the system performance stable, real good, do not need to assign someone to manage, scalability is also very good.