基于颜色和边缘特征自适应融合的人脸跟踪算法  

Face tracking algorithm of color and edge features based adaptive fusion

作　　者：周平平 万洪林[1] 刘慧[2] 李天平[1] 

机构地区：[1]山东师范大学物理与电子科学学院,山东济南250358 [2]山东财经大学计算机科学与技术学院,山东济南250014

出　　处：《中国科学技术大学学报》2017年第10期837-842,共6页JUSTC

基　　金：山东省科技发展计划项目(2014gsf116004)资助

摘　　要：针对传统的基于颜色直方图跟踪算法不能精确跟踪的缺陷,提出了一种基于粒子滤波的自适应融合多特征的人脸跟踪算法.该方法首先在视频序列中提取人脸的肤色和边缘特征,并以加权颜色直方图和边缘直方图描述人脸特征;然后采用自适应融合方法计算粒子集权重.这种自适应融合方法,有效地增强了人脸跟踪的可靠性.实验结果表明,在视频人脸存在类肤色以及光照变化等复杂背景下,该方法改善了跟踪效果并且具有较强的鲁棒性.In view of the imprecision of traditional tracking algorithms based on color histogram,a face tracking algorithm combining face multiple features based on adaptive fusion in the basic frame of particle filtering was presented.First,the color and edge features of the human face were extracted in the video sequence,while the weighted color histogram and edge orientation histogram（EOH）described facial features.Then,a self-adaptive features fusion strategy was employed to calculate particle set weight.The reliability of face tracking was enhanced by the self-adaptive features fusion strategy.Experimental results show that in the cases of complex backgrounds such as similar skin color,illumination change and so on,the proposed approach improves the tracking effect and has strong robustness.

关 键 词：人脸跟踪 粒子滤波 加权颜色直方图 边缘方向直方图 自适应融合方法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]