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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Fusion of Holistic and Part Based Features for Gender Classification in the Wild
verfasst von : Modesto Castrillón-Santana, Javier Lorenzo-Navarro, Enrique Ramón-Balmaseda
Erschienen in: New Trends in Image Analysis and Processing -- ICIAP 2015 Workshops
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Gender classification (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 classification error of the holistic approach roughly a
$$30\%$$
30
%
.