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http://hdl.handle.net/10553/20096
Title: | Fusion of holistic and part based features for gender classification in the wild | Authors: | Castrillón-Santana, Modesto Lorenzo-Navarro, Javier Ramón-Balmaseda, Enrique |
UNESCO Clasification: | 120304 Inteligencia artificial | Keywords: | Recognition Patterns Gender classification Local descriptors Score level fusion |
Issue Date: | 2015 | Publisher: | Springer | Journal: | Lecture Notes in Computer Science | Conference: | 18th International Conference on Image Analysis and Processing (ICIAP) 18th International Conference on Image Analysis and Processing, ICIAP 2015 BioFor, CTMR, RHEUMA, ISCA, MADiMa, SBMI, and QoEM |
Abstract: | Gender classi cation (GC) in the wild is an active area of current research. In this paper, we focus on the combination of a holistic state of the art approach based on features extracted from the facial pattern, with patch based approaches that focus on inner facial areas. Those regions are selected for being relevant to the human system according to the psychophysics literature: the ocular and the mouth areas. The resulting proposed GC system outperforms previous approaches, reducing the classi cation error of the holistic approach roughly a 30%. | URI: | http://hdl.handle.net/10553/20096 | ISBN: | 978-3-319-23221-8 | ISSN: | 0302-9743 | DOI: | 10.1007/978-3-319-23222-5_6 | Source: | New Trends in Image Analysis and Processing -- ICIAP 2015 Workshops. ICIAP 2015. Lecture Notes in Computer Science, v. 9281 LNCS, p. 43-50 |
Appears in Collections: | Capítulo de libro |
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