Research On Detection And Tracking Of Moving Object In Intelligent Viedo Surveillance System

Intelligent video surveillance is one of the main content in the field of pattern recognition and computer vision, which has been widely applied in military, medicine and scientific research etc. The design of Moving target detection and tracking algorithm become a core in the intelligent video surveillance system. Therefore, the study of the key technology in intelligent video surveillance system and to improve the performance of the system is of great significance.The thesis studied the main problem of the target detection and tracking algorithm, and gives the solution to the corresponding problem. The main research work in this article as follows:On the research of the motion detection, firstly three main algorithms of motion detection which is Optical flow method, the background difference method, inter-frame difference method are researched, the thesis focus on the three differential algorithm. The experimental results show that the region of moving targets aren't integrity, there is a certain shadow, inanition and so on. In order to completely and accurately detect moving targets, the thesis gives a new target detection method based on the five differential, this target detection method is the improvement based on original three differential. The experiment compared the detection effect of the standards three differential, increasing image pre-processing on three differential and five differential detection. The experimental results show the five differential can effectively eliminate the phenomenon of shadow and inanition, more completely extract the target, and make a good foundation for the back of Target Feature Extraction.On the research of object tracking, the use of projection and the first moment to pinpoint the target's centroid. The thesis integrated use of the target centroid, and moment characteristics of the area as the target characteristics, effectively described the target, and gives the matching algorithm based on the European-style distance. The thesis establish the motion model using Kalman filter, forecast the Possible location in the next frame of the tracked goal, and determine the scope of the search, and then combined with the goal matching algorithm of this paper, effectively track moving targets. Finally, research on the occlusion of more targets, and gives target tracking method in case of shelter. The thesis did the experiment simulation to tracking algorithm, and gave the experimental data and analyzed. The experimental results show that target tracking model accord with actual situation based on Kalman filter, the tracking algorithm can reliably predict the movement and track the target trajectory.Finally, combined with the improved methods of moving target detection and tracking model based on Kalman filter, using VC + + development platform and OpenCV algorithms library designed a demonstration of intelligent monitoring system. Through the demonstration of the system initially verify the feasibility and achievability of the algorithm.