Presentation 2014-05-23
3D facial shape analysis based on statistical learning methods
Misae NAKATSU, Xian-Hua HAN, Ryosuke KIMURA, Yen-Wei CHEN,
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Abstract(in English) Recently, the relationship between gene and the facial morphology attracts substantial attention. A generic framework for analyzing facial morphology variation using scanned 3D landmarks was proposed in our previous work, which mainly includes three steps: registration and landmark correspondence, statistical analysis of 3D facial shape, ancestral classification using facial features. However, the used landmark corresponding method in the previous work was based on non-rigid transformation, which is very complicated and has high computational-cost, and the classification accuracy was less than 70%, which still has large space to be improved. This study proposes a simple and fast landmark corresponding strategy using cylindrical transformation; it easily adjusts the dimension of the shape representation vector. Furthermore, beside the shape variation features extracted by Principle Component Analysis (PCA), we propose a novel discriminated feature using mean hyperplane, and normalize the feature vector for reducing scale affect. Experiments on ancestral classification show that our proposed strategy can significantly improve the recognition performances compared to the conventional work.
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Keyword(in English) Facial morphology / Gene / Statistical learning / Mean hyperplane / Normalization
Paper # SIP2014-13,IE2014-13,PRMU2014-13,MI2014-13
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Conference Information
Committee PRMU
Conference Date 2014/5/15(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) 3D facial shape analysis based on statistical learning methods
Sub Title (in English)
Keyword(1) Facial morphology
Keyword(2) Gene
Keyword(3) Statistical learning
Keyword(4) Mean hyperplane
Keyword(5) Normalization
1st Author's Name Misae NAKATSU
1st Author's Affiliation Graduate school of Information Science and Engineering, Ritsumeikan University()
2nd Author's Name Xian-Hua HAN
2nd Author's Affiliation Graduate school of Information Science and Engineering, Ritsumeikan University
3rd Author's Name Ryosuke KIMURA
3rd Author's Affiliation Graduate School of Medicine, University of the Ryukyus
4th Author's Name Yen-Wei CHEN
4th Author's Affiliation Graduate school of Information Science and Engineering, Ritsumeikan University
Date 2014-05-23
Paper # SIP2014-13,IE2014-13,PRMU2014-13,MI2014-13
Volume (vol) vol.114
Number (no) 41
Page pp.pp.-
#Pages 6
Date of Issue