Presentation 2022-02-22
Enhancing Personalized Food Image Classifier by Visual Attention and Class-Dependent Weighting
Seum Kim, Yoko Yamakata, Kiyoharu Aizawa,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In a real-world setting, food records are very noisy and strongly imbalanced. Besides, inter-class similarity and intra-class diversity problems caused by various kinds of dishes make food image classification tasks more challenging. The recent works mostly focus on solving these problems by using a user-specific classification method. In this paper, we propose a personalized food image classifier that applies visual attention and class-dependent weighting methods to records for handling the data noise and the class-specific problems. As a result, the proposed method considerably outperforms prior personalized food image classifiers and achieves a significant improvement in top-1 accuracy by up to 3.34% compared to the baseline method.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Food image recognitionpersonalizationfeature weightingfood record
Paper # ITS2021-47,IE2021-56
Date of Issue 2022-02-14 (ITS, IE)

Conference Information
Committee IE / ITS / ITE-AIT / ITE-ME / ITE-MMS
Conference Date 2022/2/21(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English) Image Processing, etc.
Chair Kazuya Kodama(NII) / Masahiro Fujii(Utsunomiya Univ.) / Hisaki Nate(Tokyo Polytechnic Univ.) / Hiroyuki Arai(Nippon Inst. of Tech.) / Kenji Machida(NHK)
Vice Chair Hiroyuki Bandoh(NTT) / Toshihiko Yamazaki(Univ. of Tokyo) / Kohei Ohno(Meiji Univ.) / Naohisa Hashimoto(AIST) / / Shogo Muramatsu(Niigata Univ.)
Secretary Hiroyuki Bandoh(KDDI Research) / Toshihiko Yamazaki(Nagoya Inst. of Tech.) / Kohei Ohno(Akita Prefectural Univ.) / Naohisa Hashimoto(NIT, Tsuruoka College) / / Shogo Muramatsu(NHK) / (Hokkaido Univ.)
Assistant Shunsuke Iwamura(NHK) / Shinobu Kudo(NTT) / Msataka Imao(Mitsubishi Electric) / Kenshi Saho(Toyama Prefectural Univ.) / Keiji Jimi(Gunma Univ.)

Paper Information
Registration To Technical Committee on Image Engineering / Technical Committee on Intelligent Transport Systems Technology / Technical Group on Artistic Image Technology / Technical Group on Media Engineering / Technical Group on Multi-media Storage
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Enhancing Personalized Food Image Classifier by Visual Attention and Class-Dependent Weighting
Sub Title (in English)
Keyword(1) Food image recognitionpersonalizationfeature weightingfood record
1st Author's Name Seum Kim
1st Author's Affiliation The University of Tokyo(UTokyo)
2nd Author's Name Yoko Yamakata
2nd Author's Affiliation The University of Tokyo(UTokyo)
3rd Author's Name Kiyoharu Aizawa
3rd Author's Affiliation The University of Tokyo(UTokyo)
Date 2022-02-22
Paper # ITS2021-47,IE2021-56
Volume (vol) vol.121
Number (no) ITS-373,IE-374
Page pp.pp.133-138(ITS), pp.133-138(IE),
#Pages 6
Date of Issue 2022-02-14 (ITS, IE)