Research On Technologies Of Intelligent Surveillance Based On Computer Vision

With the development of Computer Vision Technology, the intelligence video surveillance based on the computer vision has been widely applied. Compared with traditional video surveillance, its function has got the essential changed. It not only expand the original function biggest, but reduce the caption invested in the video surveillance. The key technologies in intelligence video surveillance has been searched in this paper, and also the video surveillance with practical application function has been implemented under the fixed camera.Moving object detection is the first and most important step in the system, the quality of detected object will affect directly the classification of object and object's behaviors understanding. Therefore the information of the object must completeness as far as possible. Background subtraction is used in this paper. The method of background modeling which is the key has been studied. The method of single Gaussian model with mixture Gaussian model can segment the moving targets accurately.It is also able to reduce time and outside influences which disproved by experiment.Target classification is an active field of computer vision, which applied widely on many fields such as intelligence video surveillance, intelligent robot and medical image analysis. Via target classification, target can be classified into different category which predefined, and then understand objects behaviors. Based on the minimum error Bayes decision, occupy-space-proportion, the ratio of height to width, and principal axis of inertia direction are used to classification by obtained the mean value and variance through experiment.Kalman filter is used to track the target in this paper. This algorithm can predict moving information using the existing movement, and track accurately. The occlusion which is difficult in tracking is researched in this paper. And a new method which used target's area to confirm the point at which occlusion occurs and prediction its moving path is presented to prevent the loss. The experiment results show that this method can solve the problem which the target occurred short occlusion. And the specific area surveillance is also searched in this paper.