Pose estimation based on human detection and segmentation  

作　　者：CHEN Qiang ZHENG EnLiang LIU YunCai 

机构地区：[1]Institute of image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200240, China

出　　处：《Science in China(Series F)》2009年第2期244-251,共8页中国科学（F辑英文版）

基　　金：Supported by the National Basic Research Program of China (Grant No.2006CB303103);Key Program of the National Natural Science Foundation of China (Grant No.60833009)

摘　　要：We address the problem of 3D human pose estimation in a single real scene image. Normally, 3D pose estimation from real image needs background subtraction to extract the appropriate features. We do not make such assumption, In this paper, a two-step approach is proposed, first, instead of applying background subtraction to get the segmentation of human, we combine the segmentation with human detection using an ISM-based detector. Then, silhouette feature can be extracted and 3D pose estimation is solved as a regression problem. RVMs and ridge regression method are applied to solve this problem. The results show the robustness and accuracy of our method.We address the problem of 3D human pose estimation in a single real scene image. Normally, 3D pose estimation from real image needs background subtraction to extract the appropriate features. We do not make such assumption, In this paper, a two-step approach is proposed, first, instead of applying background subtraction to get the segmentation of human, we combine the segmentation with human detection using an ISM-based detector. Then, silhouette feature can be extracted and 3D pose estimation is solved as a regression problem. RVMs and ridge regression method are applied to solve this problem. The results show the robustness and accuracy of our method.

关 键 词：human detection and segmentation 3D pose estimation regression machine learning 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]