东南大学学报（英文版）2007，Vol.23Issue(2)：196-201,6.
基于均值移动重要性采样的粒子滤波人脸跟踪算法
Face tracking algorithm based on particle filter with mean shift importance sampling
摘要
Abstract
The condensation tracking algorithm uses a prior transition probability as the proposal distribution,which does not make full use of the current observation. In order to overcome this shortcoming, a new face tracking algorithm based on particle filter with mean shift importance sampling is proposed. First, the coarse location of the face target is attained by the efficient mean shift tracker, and then the result is used to construct the proposal distribution for particle propagation. Because the particles obtained with this method can cluster around the true state region, particle efficiency is improved greatly. The experimental results show that the performance of the proposed algorithm is better than that of the standard condensation tracking algorithm.关键词
人脸跟踪/粒子滤波/重要性采样/condensation/均值移动Key words
face tracking/particle filter/importance sampling/condensation/mean shift分类
信息技术与安全科学引用本文复制引用
高建坡,杨浩,安国成,吴镇扬..基于均值移动重要性采样的粒子滤波人脸跟踪算法[J].东南大学学报（英文版）,2007,23(2):196-201,6.基金项目
The National Natural Science Foundation of China(No. 60672094). （No. 60672094）
