Font Size: a A A

Research On The Key Technologies Of Computer Intelligent Video Surveillance System

Posted on:2006-10-21Degree:DoctorType:Dissertation
Country:ChinaCandidate:S FangFull Text:PDF
GTID:1118360155458146Subject:Control theory and control engineering
Abstract/Summary:PDF Full Text Request
Computer intelligent video surveillance system(CIVSS) is one of new arising high-tech application fields. It spans many subjects including computer science, machine vision, image engineering, pattern analysis, artificial intelligence, etc. CIVSS can automatically analyse sequence image by the methods of computer vision and video analysis. The system can real-time detect, recognize, and track moving objects in a special environment. Furthermore, it can also analyse and judge the behavior of objects. The aims of CIVSS are to understand the meanings of video stream and to explain the scenes comprehensibly, hence to guide the action and make some decision.Surveillance cameras are already applied in safety monitoring, fire monitoring, traffic flow and peccancy, and the surveillance for bank, shopping, parking lots, aerodrome, underground, etc. But video data currently is used only "after the fact" as a forensic tool, thus losing its primary benefit as an active, real-time medium. If the current video surveillance system can be improved into a CIVSS, video surveillance will largely enhance quality and economize investment in the same time.As to computer intelligent video surveillance, there are still many problems no matter in theory research or in applications. Large numbers of researchers devoted themselves in the area and have already achieved many progresses. The dissertation studied the key technologies of CIVSS based on the current conclusion. The main contributions of this dissertation can be summarized as followings:Firstly, object detection technologies are investigated. A moving object detection algorithm based on background modeling is proposed. Statistical models of color and color gradients are built, which are real-time updated. The two models are used together to detect moving object. The algorithm can effectively deal with the problems of the abstraction and update of background, background disturbance, illumination changes etc.Secondly, object-tracking technologies are introduced. A multi-target tracking...
Keywords/Search Tags:computer intelligent video surveillance, moving object detection, object tracking, object classification, behavior understanding, mixture Gaussian model, Bayesian estimation, feature selection, support vector machine
PDF Full Text Request
Related items