Efficient Human Parsing based on Sketch Representation

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	Efficient Human Parsing based on Sketch Representation
	Meng Wang; Zhaoxiang Zhang; Yunhong Wang
	2012-11-05
会议名称	Asian Conference on Computer Vision
会议录名称	ACCV 2012
会议日期	5-9 November 2012
会议地点	Daejeon, Korea
摘要	In this paper, we present an efficient human parsing method which estimates human body poses from 2D images. Firstly we propose an edge sketch representation, which enhance critical information for pose estimation and prune the redundant. The sketch representation is generated by employing two sets of filters on extracted edges. Based on sketch representation, body part candidates can be located easily using parallel lines detection in Hough space. Then we use specifically trained linear SVM classifiers to detect each body part candidates based on parallel line feature. A dynamic programming algorithm is applied to calculate the MAP estimation based on standard pictorial structure model, which use a kinematic tree to describe human pose. To evaluate the representing ability of proposed sketch representation, as well as the accuracy and efficiency of our entire human pose estimation method, we run two sets of experiments on a sports image dataset respectively. Experimental results demonstrate that the human body parts in the images can be well described by our proposed sketch representation. Furthermore, our human pose estimation method is efficient and achieves comparable accuracy against the state-of-the-art.
关键词	Parsing Representation
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/13266
专题	智能感知与计算研究中心
通讯作者	Zhaoxiang Zhang
推荐引用方式 GB/T 7714	Meng Wang,Zhaoxiang Zhang,Yunhong Wang. Efficient Human Parsing based on Sketch Representation[C],2012.