![](/images/graphics-bg.png)
Gender Recognition from Unconstrained and Articulated Human Body
Joint Authors
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-07
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
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 articulatedhuman 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.
American Psychological Association (APA)
Wu, Qin& Guo, Guodong. 2014. Gender Recognition from Unconstrained and Articulated Human Body. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1049912
Modern Language Association (MLA)
Wu, Qin& Guo, Guodong. Gender Recognition from Unconstrained and Articulated Human Body. The Scientific World Journal No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1049912
American Medical Association (AMA)
Wu, Qin& Guo, Guodong. Gender Recognition from Unconstrained and Articulated Human Body. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1049912
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049912