International Conference on Image Analysis and Processing

ICIAP 2015: New Trends in Image Analysis and Processing -- ICIAP 2015 Workshops pp 43-50

Fusion of Holistic and Part Based Features for Gender Classification in the Wild

  • Modesto Castrillón-Santana
  • Javier Lorenzo-Navarro
  • Enrique Ramón-Balmaseda
Conference paper

DOI: 10.1007/978-3-319-23222-5_6

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9281)
Cite this paper as:
Castrillón-Santana M., Lorenzo-Navarro J., Ramón-Balmaseda E. (2015) Fusion of Holistic and Part Based Features for Gender Classification in the Wild. In: Murino V., Puppo E., Sona D., Cristani M., Sansone C. (eds) New Trends in Image Analysis and Processing -- ICIAP 2015 Workshops. ICIAP 2015. Lecture Notes in Computer Science, vol 9281. Springer, Cham

Abstract

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 \(30\%\).

Keywords

Gender classification Local descriptors Score level fusion 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Modesto Castrillón-Santana
    • 1
  • Javier Lorenzo-Navarro
    • 1
  • Enrique Ramón-Balmaseda
    • 1
  1. 1.Universidad de Las Palmas de Gran CanariaLas Palmas de Gran CanariaSpain

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