Design And Implementation Of Human Activity Recognition System Based On Wavelet Moment

Visual analysis of human motion from video sequences has been attached more and more importance to computer visions in the recent years. Along with the time progress, this technology also in the unceasing development and consummation, so it will certainly have the broad application prospect and bring the huge economic efficiency for the society in the future.Firstly this paper introduces the research status and tendency of human motion recognition at home and abroad, and then analyses its application in Security Monitoring System. In this foundation, the work in the thesis makes three main contributions in the field:On the research of the moving objects detection and extraction under a static background, we summarize several current algorithms and propose an improved algorithm. Combining the Background Subtraction and Temporal difference, then we can get more precise moving human contour.On the research of moving objects tracking, this paper analyzes the current tracking algorithms. Then a tracking algorithm suitable for this system is introduced in detail, which uses Kalman Filter to track the moving objects real-timely in the scenes,In the aspect of human motion recognition, because of the fact that human continuous motion can be decomposed into an image sequence based on time, state space method is applied in this paper. Firstly this paper uses wavelet moment to extract features of the human body images, and then recognizes the moving human bodies activity based on Hidden Markov Model.Through the experiment, the algorithm has very small leak-examining and mistake-examining-rate, moreover it has good real time.