Abstract：Human pose estimation is an essential issue in computer vision area since it has many applications such as human activity analysis, human computer interaction and visual surveillance. In this paper, 2D human estimation issue in monocular images and videos is addressed. The observation model and the inference method are improved based on part based graph inference method. A rotation invariant edge field feature is designed and based on which a Boosting classifier is learnt as the observation model. The human pose estimation is done with a particle based belief propagation inference method. Experiments show the effectiveness and the speed of the proposed method.
苏延超, 艾海舟, 劳世竑. 图像和视频中基于部件检测器的人体姿态估计[J]. 电子与信息学报, 2011, 33(6): 1413-1419.
Su Yan-Chao, Ai Hai-Zhou, Lao Shi-Hong. Part Detector Based Human Pose Estimation in Images and Videos. , 2011, 33(6): 1413-1419.
2011, Vol. 33 
