title: Gender recognition from unconstrained and articulated human body.
abstract: Gender recognition has many useful applications, ranging from business intelligence to image search and social activity analysis. Traditional research on gender recognition focuses on face images in a constrained environment. This paper proposes a method for gender recognition in articulated human body images acquired from an unconstrained environment in the real world. A systematic study of some critical issues in body-based gender recognition, such as which body parts are informative, how many body parts are needed to combine together, and what representations are good for articulated body-based gender recognition, is also presented. This paper also pursues data fusion schemes and efficient feature dimensionality reduction based on the partial least squares estimation. Extensive experiments are performed on two unconstrained databases which have not been explored before for gender recognition.
authors: Department of Computer Science, Jiangnan University, Wuxi, Jiangsu 214122, China ; Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA.
authors: Qin
authors: Q
authors: Wu
authors: Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA.
authors: Guodong
authors: G
authors: Guo
mesh_terms: D000465:Algorithms; D001699:Biometry / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D010781:Photography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012732:Sex Determination Analysis / Q000379:methods*; D051598:Whole Body Imaging / Q000379:methods*