Research On Moving Tracking Technique For Human Joints

Video human motion analysis is a very promising research area which combines subjects of computer vision, artificial intelligence, pattern recognition, image processing, and so on. Thus this work is an interdisciplinary and challenging research topic. Tracking human motion from image sequences is main task for human motion analysis. Due to the essential of human motion is the bone of movement around human joints, thus the tracking techniques of human joints are most representative in the human motion tracking. The tracking technique of the veracity human joints is a research topic which has a wide range of applications in athlete action analysis, computer-aided clinical diagnosis, computer animation, and so on.For the difficult problems of human joints tracking, the tracking techniques of human joints movement are researched in the dissertation.The kernel density estimation and the Mean Shift theory of nonparametric density estimation are studied in this dissertation. Then the application of Mean Shift algorithm (MSA) in the targets tracking is researched. Aiming at the motion process of the targets, the template update is needed when its own conditions changes. The condition and method of template update are studied. The Bhattacharyya distance between the human joints as the condition of template update, at the same time, the weighted new and old template of update method is put forward for the Mean Shift in this dissertation. The traditional Mean Shift is improved the tracking precision of the moving human joints.For the unreliability of single color character in the traditional MSA when targets are influenced by the illumination and other environmental conditions, diversified moment invariants are researched and a tracking method of human joints movement based on Mean Shift is proposed. The velocity, wavelet moment invariants and color distribution characteristic are utilized by the proposed algorithm, in which the tracking inaccuracy by the illumination effect is greatly reduced. In the mean time, this new algorithm has the tolerant ability for the occlusion of the moving targets.The research based on Kalman Filter (KF) is adopted to reduce the search range of human joints, and the tracking algorithm based on Kalman Filter and Mean Shift is brought forward. In current frame, Kalman Filter is adequately used to forecast the possible positions of human joints, and the advantages of wavelet moment invariants and color distribution in the targets tracking are played by the proposed algorithm. The method can decreases the iterative operation, but offers an effective approach to improve the searching efficiency.The tracking algorithm of the targets is researched for the multi-mode, non-Gaussian distribution and nonlinear problem by the occlusion. And aiming at the single feature information of the target, the robust tracking can not be completed. Thus a tracking algorithm of human joints motion is proposed, in which the observation model based on the character information is included in the unscented particle filter (UPF). The multi-hypothesis and the latest observation information of UPF are made the best of the proposed method. Experiment results demonstrate that the human joints tracking algorithm based on feature information and UPF is proposed in the dissertation, which can settles well the tracking problem for the targets of the frequent occlusions, and have good robust.Aiming at a longer time occlusion in the moving process of human joints, the sample impoverishment phenomenon of the unscented particle filter is produced. And the diversity of sample collection needs be added. So the intelligence optimization algorithm is researched and a tracking algorithm of moving human joints based on intelligence optimization and UPF is put forward. The sample impoverishment phenomenon is improved by the proposed tracking algorithm in this dissertation.This dissertation makes deeply research on the Mean Shift,Particle Filter (PF),Unscented Particle Filter and intelligence optimization algorithm. And some beneficial results are obtained. These results give the important effect for the veracity, robust and reliable tracking of the moving human joints.