IEICE TRANSACTIONS on Information
Estimation of the Attractiveness of Food Photography Based on Image Features
Summary :
We introduce a method to estimate the attractiveness of a food photo. It extracts image features focusing on the appearances of 1) the entire food, and 2) the main ingredients. To estimate the attractiveness of an arbitrary food photo, these features are integrated in a regression scheme. We also constructed and released a food image dataset composed of images of ten food categories taken from 36 angles and accompanied with attractiveness values. Evaluation results showed the effectiveness of integrating the two kinds of image features.
- Publication
- IEICE TRANSACTIONS on Information Vol.E102-D No.8 pp.1590-1593
- Publication Date
- 2019/08/01
- Publicized
- 2019/05/07
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2018EDL8219
- Type of Manuscript
- LETTER
- Category
- Human-computer Interaction
Authors
Kazuma TAKAHASHI
Nagoya University
Tatsumi HATTORI
Chukyo University
Keisuke DOMAN
Chukyo University
Yasutomo KAWANISHI
Nagoya University
Takatsugu HIRAYAMA
Nagoya University
Ichiro IDE
Nagoya University
Daisuke DEGUCHI
Nagoya University
Hiroshi MURASE
Nagoya University
Keyword
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Kazuma TAKAHASHI, Tatsumi HATTORI, Keisuke DOMAN, Yasutomo KAWANISHI, Takatsugu HIRAYAMA, Ichiro IDE, Daisuke DEGUCHI, Hiroshi MURASE, "Estimation of the Attractiveness of Food Photography Based on Image Features" in IEICE TRANSACTIONS on Information,
vol. E102-D, no. 8, pp. 1590-1593, August 2019, doi: 10.1587/transinf.2018EDL8219.
Abstract: We introduce a method to estimate the attractiveness of a food photo. It extracts image features focusing on the appearances of 1) the entire food, and 2) the main ingredients. To estimate the attractiveness of an arbitrary food photo, these features are integrated in a regression scheme. We also constructed and released a food image dataset composed of images of ten food categories taken from 36 angles and accompanied with attractiveness values. Evaluation results showed the effectiveness of integrating the two kinds of image features.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2018EDL8219/_p
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@ARTICLE{e102-d_8_1590,
author={Kazuma TAKAHASHI, Tatsumi HATTORI, Keisuke DOMAN, Yasutomo KAWANISHI, Takatsugu HIRAYAMA, Ichiro IDE, Daisuke DEGUCHI, Hiroshi MURASE, },
journal={IEICE TRANSACTIONS on Information},
title={Estimation of the Attractiveness of Food Photography Based on Image Features},
year={2019},
volume={E102-D},
number={8},
pages={1590-1593},
abstract={We introduce a method to estimate the attractiveness of a food photo. It extracts image features focusing on the appearances of 1) the entire food, and 2) the main ingredients. To estimate the attractiveness of an arbitrary food photo, these features are integrated in a regression scheme. We also constructed and released a food image dataset composed of images of ten food categories taken from 36 angles and accompanied with attractiveness values. Evaluation results showed the effectiveness of integrating the two kinds of image features.},
keywords={},
doi={10.1587/transinf.2018EDL8219},
ISSN={1745-1361},
month={August},}
Copy
TY - JOUR
TI - Estimation of the Attractiveness of Food Photography Based on Image Features
T2 - IEICE TRANSACTIONS on Information
SP - 1590
EP - 1593
AU - Kazuma TAKAHASHI
AU - Tatsumi HATTORI
AU - Keisuke DOMAN
AU - Yasutomo KAWANISHI
AU - Takatsugu HIRAYAMA
AU - Ichiro IDE
AU - Daisuke DEGUCHI
AU - Hiroshi MURASE
PY - 2019
DO - 10.1587/transinf.2018EDL8219
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E102-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2019
AB - We introduce a method to estimate the attractiveness of a food photo. It extracts image features focusing on the appearances of 1) the entire food, and 2) the main ingredients. To estimate the attractiveness of an arbitrary food photo, these features are integrated in a regression scheme. We also constructed and released a food image dataset composed of images of ten food categories taken from 36 angles and accompanied with attractiveness values. Evaluation results showed the effectiveness of integrating the two kinds of image features.
ER -
English
