Presentation 2012-06-28
Estimating the Clothes Characteristics with the Image and Depth Sensors for Developing Virtual Fitting Room
Yuka MATSUBA, Hiroyuki FUNAYA, Akihiro NAKAMURA, Kazushi IKEDA,
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Abstract(in English) Virtual fitting rooms show customers how they would appear if they wore clothes using the clothes data and general body data input in advance. However, conventional systems cannot treat the clothes the customers own, since acquiring clothes data (form and materials) is not easy. This study is a first step to construct a virtual fitting room with a data acquisition system. We proposed a method for estimating the parameters, which are necessary for a physical simulator, from depth images and RGB images of clothes, using the simultaneous perturbation method.
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Keyword(in English) Virtual fitting room / parameter estimation / simultaneous perturbation / optimization / animation / depth image
Paper # NC2012-7
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Committee NC
Conference Date 2012/6/21(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Estimating the Clothes Characteristics with the Image and Depth Sensors for Developing Virtual Fitting Room
Sub Title (in English)
Keyword(1) Virtual fitting room
Keyword(2) parameter estimation
Keyword(3) simultaneous perturbation
Keyword(4) optimization
Keyword(5) animation
Keyword(6) depth image
1st Author's Name Yuka MATSUBA
1st Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology()
2nd Author's Name Hiroyuki FUNAYA
2nd Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology
3rd Author's Name Akihiro NAKAMURA
3rd Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology
4th Author's Name Kazushi IKEDA
4th Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology
Date 2012-06-28
Paper # NC2012-7
Volume (vol) vol.112
Number (no) 108
Page pp.pp.-
#Pages 5
Date of Issue