Intelligent Video Surveillance Of Motion Detection And Tracking

Intelligent monitoring technology have a wide range of applications in transportation,finance,security and other departments,what's more,with the development of the society,the development of the intelligent monitoring is becoming more and more important.It is an important subject in the field of computer vision research,and the moving target detection tracking is the core of the intelligent monitoring system technology.Moving target detection is defined as the study of video image sequence,and its purpose is to determine whether there is moving object in video sequences.The moving target tracking is mainly refers to tracking the detection of the target trajectory and some related parameters of the movement.In this thesis,the tracking and detection of moving targets in intelligent monitoring is taken as the research content,and it provides a basis study of the follow-up development of intelligent monitoring.In terms of moving target detection,this thesis proposes a method combining the inter-frame difference method and background difference method by comparing the advantages and disadvantages of the two methods.The experimental results show that the proposed method can improve the precision and reduce the error.For moving target tracking,the thesis adopted Cam-shift algorithm which based on Mean-shift algorithm,and the algorithm improves the Mean-shift algorithm by automatically adjusting the size of the search window to fit the size of the target..Cam-shift algorithm can solve the problem of occlusion,but because of the large displacement between frames,it will produce errors and the miss the target tracking.In the aspect of improving Cam-shift,this thesis predicts the moving object in advance by simply moving the search box to enlarge the possibility of searching frame and target connection,and improve the accuracy of tracking.