Presentation 2009-05-29
Facial Pose Image Synthesis with a Single Image Using Tensor Subspace Approximation Method
Xu Qiao, Takanori Igarashi, Keisuke Nakao, Akio Kashimoto, Yen-Wei Chen,
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Abstract(in English) In this paper we proposed a new method called tensor subspace approximation (TSA) to do the facial pose image synthesis with a single image. We make use of the morphable model to all the image data previously in order to separate the image information into two parts: shape and texture. This method applies high-dimensional PCA method which deal with the objective data in the form of tensor to estimate the identify vectors of each samples among the varied images. MaVIC Database (KAO-Ritsumeikan Multi-angle View, Illumination and Cosmetic Facial Database) is used in our experiments and results are improved the accuracy of the method.
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Keyword(in English) Facial pose image synthesis / identify feature vector / high-dimensional PCA / tensor subspace approximation
Paper # IE2009-44,PRMU2009-35,MI2009-35
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Committee IE
Conference Date 2009/5/21(1days)
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Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Facial Pose Image Synthesis with a Single Image Using Tensor Subspace Approximation Method
Sub Title (in English)
Keyword(1) Facial pose image synthesis
Keyword(2) identify feature vector
Keyword(3) high-dimensional PCA
Keyword(4) tensor subspace approximation
1st Author's Name Xu Qiao
1st Author's Affiliation College of Information and Science, Ristumeikan University()
2nd Author's Name Takanori Igarashi
2nd Author's Affiliation Beauty Cosmetic Research Lab, Kao Corporation
3rd Author's Name Keisuke Nakao
3rd Author's Affiliation Beauty Cosmetic Research Lab, Kao Corporation
4th Author's Name Akio Kashimoto
4th Author's Affiliation Beauty Cosmetic Research Lab, Kao Corporation
5th Author's Name Yen-Wei Chen
5th Author's Affiliation College of Information and Science, Ristumeikan University
Date 2009-05-29
Paper # IE2009-44,PRMU2009-35,MI2009-35
Volume (vol) vol.109
Number (no) 63
Page pp.pp.-
#Pages 6
Date of Issue