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| Content Provider | PubMed Central |
|---|---|
| Author | Qin, Wu Guo, Guodong |
| Copyright Year | 2014 |
| 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 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. |
| Related Links | http://dx.doi.org/10.1155/2014/513240 |
| Starting Page | 513240 |
| File Format | |
| ISSN | 23566140 |
| e-ISSN | 1537744X |
| Journal | The Scientific World Journal |
| Volume Number | 2014 |
| Language | English |
| Publisher | Hindawi Publishing Corporation |
| Publisher Date | 2014-01-01 |
| Access Restriction | Open |
| Rights Holder | Hindawi Publishing Corporation |
| Subject Keyword | Biochemistry, Genetics and Molecular Biology(all) Environmental Science(all) Medicine(all) Research in Higher Education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Medicine Biochemistry, Genetics and Molecular Biology Environmental Science |
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