An analysis of automatic gender classification

Authors:
Modesto Castrillón-Santana;Quoc C. Vuong
Affiliations:
IUSIANI, Edificio Central del Parque Científico-Tecnológico, Universidad de Las Palmas de Gran Canaria, Las Palmas, Spain;Division of Psychology, Henry Wellcome Building for Neuroecology, Newcastle University, Newcastle upon Tyne, UK
Venue:
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Year:
2007

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Abstract

Different researches suggest that inner facial features are not the only discriminative features for tasks such as person identification or gender classification. Indeed, they have shown an influence of features which are part of the local face context, such as hair, on these tasks. However, object-centered approaches which ignore local context dominate the research in computational vision based facial analysis. In this paper, we performed an analysis to study which areas and which resolutions are diagnostic for the gender classification problem. We first demonstrate the importance of contextual features in human observers for gender classification using a psychophysical "bubbles" technique. The success rate achieved without internal facial information convinced us to analyze the performance of an appearance-based representation which takes into account facial areas and resolutions that integrate inner features and local context.