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Title: An analysis of automatic gender classification
Authors: Castrillón-Santana, Modesto 
Vuong, Quoc C.
UNESCO Clasification: 120304 Inteligencia artificial
Issue Date: 2007
Project: Tecnicas Para El Robustecimiento de Procesos en Vision Artificial Para la Interaccion 
Journal: Lecture Notes in Computer Science 
Conference: 12th Iberoamerican Congress on Pattern Recognition 
12th Iberoamerican Congress on Pattern Recognition, CIARP 2007 
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.
ISBN: 978-3-540-76724-4
ISSN: 0302-9743
DOI: 10.1007/978-3-540-76725-1_29
Source: Rueda L., Mery D., Kittler J. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2007. Lecture Notes in Computer Science, vol 4756. Springer, Berlin, Heidelberg
Appears in Collections:Actas de congresos
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