Two-Dimensional Human Body Joint Tracking Method Research Integrated In Head-Shoulder Three Dimensional Model

Human motion tracking is an activated an important research domain in human motion analysis. Meanwhile, human joint tracking is an important part of Human motion tracking. The subject of this paper is just tracking all the 14 joints of human body.First, this paper tries to do the tracking job directly by developing a two-dimensional articulated body model, based on which, Particle filtering is used to finish this task. But when Particle filtering is used to do multi-target tracking, it's to encountering the problem of "particle-explosion". In order to solve the problem, the tactic of partitioned sampling is adopted to optimize the tracking algorithm. If the tracking method only use color histogram matching, the "shrinking" problem which is caused by the freedom of the particles from two different sets arises. In this research, customized physical distance constraints, which can reflect the physical structure information, is proposed originally to limit and even avoid the "shrinking" problem. However, the error of head is so clear that it can accumulate constantly in the top-down tracking tactic. Potentially, the tracking error of the other joints is increased in the process, which encourages an idea of a special head track processing.Then, this paper proposes a head tracking method based on three-dimensional model. The method also need to build a three-dimensional head-shoulder model, which can also reflect the head structure information of human and is different to any other human body. Two-dimensional image template is got by planar projection of the three-dimensional model. And the tracking method is just done by matching the observation and the two-dimensional template. This tracking algorithm doesn't need any initialization. Before matching, by background substraction, binarization and edge detection on the observation, it's easy to obtain ROI which comprises the head region of human. When matching, edge information is used to construct likelihood function.At last, this paper builds mixture double model by introducing the three-dimensional head-shoulder model to the two-dimensional articulated model and based on the new model, fulfills the joint tracking of all the body. In which, the head and the two shoulders is tracked by three-dimensional head-shoulder model, and then the tracking result of the head and the two shoulders is used as constant to assist the two-dimensional articulated model for the tracking of other joints. Abundantly, The mixture double model absorbs the advantage of fast computing and high accuracy of the tracking method based on three-dimensional head-shoulder model which uses template matching algorithm. Meanwhile, it inherits the availability of applying the joint tracking of the whole body.