Automatic Body Feature Extraction from Front and Side Images  

作　　者：Lingyan Jiang Jian Yao Baopu Li Fei Fang Qi Zhang Max Q.-H. Meng 

机构地区：[1]Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, P.R. China [2]School of Computer, Electronics and Information, Guangxi University, Nanning, Guangxi, P.R. China [3]School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, Hubei, P.R. China [4]Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, P.R. China

出　　处：《Journal of Software Engineering and Applications》2012年第12期94-100,共7页软件工程与应用（英文）

摘　　要：Human body feature extraction based on 2D images provides an efficient method for many applications, e.g. non-contact body size measurements, constructing 3D human model and recognizing human actions. In this paper a systematic approach is proposed to detect feature points of human body automatically from its front and side images. Firstly, an efficient approach for silhouette and contour detection is used to represent the contour curves of a human body shape with Freeman’s 8-connected chain codes. The contour curves are considered as a number of segments connected together. Then, a series of feature points on human body are extracted based on the specified rules by measuring the differences between the directions of the segments. In total, 101 feature points with clearly geometric properties (that rather accurately reflect the bump or turning of the contours) are extracted automatically, including 27 points corresponding to the definitions of the landmarks about garment measurements. Finally, the proposed approach was tested on ten human subjects and the entire 101 feature points with specific geography geometrical characteristics were correctly extracted, indicating an effective and robust performance.Human body feature extraction based on 2D images provides an efficient method for many applications, e.g. non-contact body size measurements, constructing 3D human model and recognizing human actions. In this paper a systematic approach is proposed to detect feature points of human body automatically from its front and side images. Firstly, an efficient approach for silhouette and contour detection is used to represent the contour curves of a human body shape with Freeman’s 8-connected chain codes. The contour curves are considered as a number of segments connected together. Then, a series of feature points on human body are extracted based on the specified rules by measuring the differences between the directions of the segments. In total, 101 feature points with clearly geometric properties (that rather accurately reflect the bump or turning of the contours) are extracted automatically, including 27 points corresponding to the definitions of the landmarks about garment measurements. Finally, the proposed approach was tested on ten human subjects and the entire 101 feature points with specific geography geometrical characteristics were correctly extracted, indicating an effective and robust performance.

关 键 词：SILHOUETTE detection CONTOUR representation Human FEATURE point EXTRACTION 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]