For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
Sexual Dimorphism Analysis and Gender Classification in 3D Human Face
Yuan HU Li LU Jingqi YAN Zhi LIU Pengfei SHI
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2010/09/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Pattern Recognition
gender classification, sexual dimorphism, SVMs, 3D face classification,
Full Text: PDF(626.6KB)
>>Buy this Article
In this paper, we present the sexual dimorphism analysis in 3D human face and perform gender classification based on the result of sexual dimorphism analysis. Four types of features are extracted from a 3D human-face image. By using statistical methods, the existence of sexual dimorphism is demonstrated in 3D human face based on these features. The contributions of each feature to sexual dimorphism are quantified according to a novel criterion. The best gender classification rate is 94% by using SVMs and Matcher Weighting fusion method. This research adds to the knowledge of 3D faces in sexual dimorphism and affords a foundation that could be used to distinguish between male and female in 3D faces.