结合粒子滤波和局部优化方法的人体运动跟踪

Combining Particle Filter with Local Optimization for Human Body Tracking

提出一种将粒子滤波和局部优化相结合的算法框架,用于解决多关节人体运动跟踪问题·由于高维空间中无法进行密集采样,因此普通的粒子滤波方法对于人体运动估计存在困难·在粒子滤波过程中引入局部优化方法来减少样本个数:一方面,对每个样本进行局部优化得到更加匹配的状态;另一方面,优化后的结果被用来指导下一时刻采样函数的生成·实验结果表明,该方法能够以较少的样本完成三维人体运动跟踪任务·

movement A new framework combining particle filter with local optimization is proposed to solve the tracking of articulated human model. General particle filter does not fit with the high dimension human body tracking, where the dense sampling strategy is impossible. The local optimization algorithm is introduced into the framework of particle filter to .solve this problem. First of all, each sample is optimized according to the observation likelihood model; second, the optimized result is used to guide the sampling step at the next time. The experiment shows that our proposed algorithm, using very few samples, can track the three dimensional pose of human body successfully.