Human motion tracking based on statistical model and genetic particle filter
基于统计模型的遗传粒子滤波器人体运动跟踪*

A method of human motion tracking was presented,which was based on statistical model and genetic particle filter.The local binary pattern was introduced to extract the texture feature.And to solve the selfocclusion problem,the similarity was expressed by the sum of the weighted color and texture histogram similarity.The human silhouette was exactly presented by a statistical model,and through the variable shape parameter the shape vector of the object could be get.The genetic particle filter was used as the tracking method to improve the robustness and precision.First,the variable shape parameter could be predicted and updated in genetic particle filter,and then through the connection between the variable shape parameter and the shape vector of the object,the human silhouette in the image sequence could be get.This method could effectively reduce the computation cost and realize the purpose that tracks the human motion quickly and exactly.Finally,it also performed some experiments,and proved that the method works effectively.