Multimodal Facial Gender and Ethnicity Identification

  • Xiaoguang Lu
  • Hong Chen
  • Anil K. Jain
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3832)

Abstract

Human faces provide demographic information, such as gender and ethnicity. Different modalities of human faces, e.g., range and intensity, provide different cues for gender and ethnicity identifications. In this paper we exploit the range information of human faces for ethnicity identification using a support vector machine. An integration scheme is also proposed for ethnicity and gender identifications by combining the registered range and intensity images. The experiments are conducted on a database containing 1240 facial scans of 376 subjects. It is demonstrated that the range modality provides competitive discriminative power on ethnicity and gender identifications to the intensity modality. For both gender and ethnicity identifications, the proposed integration scheme outperforms each individual modality.

Keywords

Support Vector Machine Face Recognition Gesture Recognition Range Image Ethnicity Identification 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Xiaoguang Lu
    • 1
  • Hong Chen
    • 1
  • Anil K. Jain
    • 1
  1. 1.Michigan State UniversityEast Lansing

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