基于复合时空特征的人体行为识别方法  

Human Action Recognition Based on Composite Spatio-Temporal Features

作　　者：秦华标[1] 张亚宁[1] 蔡静静[1] 

机构地区：[1]华南理工大学电子与信息学院,广州510640

出　　处：《计算机辅助设计与图形学学报》2014年第8期1320-1325,共6页Journal of Computer-Aided Design & Computer Graphics

基　　金：国家自然科学基金(60972136);广东省科技计划项目(2010B010600014)

摘　　要：为了有效地表征人体行为中的姿势信息和运动信息,提高行为识别算法的准确率,提出一种融合三维方向梯度直方图特征与光流直方图特征的复合时空特征,并利用其进行人体行为识别.首先采用复合时空特征综合描述三维时空局部区域的像素分布和像素变化;然后构建复合时空特征词典,并根据该特征词典完成对人体行为序列特征集合的描述;最后采用主题模型构建人体行为识别算法,对行为序列中提取的复合时空特征进行分类,实现人体行为的识别.实验结果表明:该方法能有效地提高人体行为识别准确率.To improve the accuracy of human action recognition algorithm,a novel approach for action recognition based on composite spatio-temporal features is proposed,which combines 3Dhistograms of oriented gradients feature with histograms of optical flow feature.Firstly,the composite spatiotemporal features are used to describe the pixels distribution and pixels variance in 3Dspatio-temporal local area.Then the composite spatio-temporal feature dictionary is built and used to describe the behavior sequence feature vector.Lastly,the topic model is used to construct the human action recognition algorithm that classifies the composite features extracted from the behavior sequence,which leads to the action recognition.The experimental results show that the proposed algorithm improves the accuracy of human action recognition effectively.

关 键 词：行为识别 梯度特征 主题模型 光流特征 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]