摘要
为实现稳健和精确的人脸跟踪,充分挖掘了人脸中的颜色信息、梯度方向信息和空间结构信息。在人脸中提取眼睛、鼻子和嘴巴等显著特征子块作为跟踪子块,在每个子块中选择最显著的特征作为跟踪的依据,并用马尔科夫随机场建立各个子块之间的空间约束关系,实现稳健的人脸跟踪。和若干典型跟踪算法的比较,实验结果表明,所提出的跟踪算法具有较好的稳健性和精确性。
To achieve a robust and precise face tacking, the color information, gradient direction information and spatial structure information of face are fully exploited. The eyes, nose and mouth patches are employed as tracking regions from human face. The dominant features in these patches are extracted as the basis for tracking. Markov random fields are used to build the spatial constraints between these patches, and a robust tracking algorithm is realized. Experimental results show that, compared with several typical tracking algorithms, the proposed algorithm has well performance in robustness and precision.
出处
《激光与光电子学进展》
CSCD
北大核心
2017年第2期126-130,共5页
Laser & Optoelectronics Progress
基金
国家自然科学基金(61179011)
福建省自然科学基金(2014J01224)
关键词
图像处理
人脸跟踪
马尔科夫随机场
多特征跟踪
分块跟踪
粒子滤波
image processing
face tracking
Markov random field
multi-feature tracking
part-based tracking
particle filter
