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| Presentation | 2017-09-22 10:50 Quantitative analysis on image features for the estimation of the attractiveness of food photography -- How the composition of ingredients affects the attractiveness -- Tatsumi Hattori, Keisuke Doman (Chukyo Univ.), Ichiro Ide (Nagoya Univ.), Yoshito Mekada (Chukyo Univ.)  MVE2017-22 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | We report the results of quantitative analysis on how the composition of food ingredients affects the attractiveness of food photography. We have been focusing on some photography parameters and have proposed a method for attractiveness estimation for food photography by integrating multiple image features. It estimated the attractiveness based on regression analysis using image features as explanatory variables and attractiveness as an objective variable. Although we confirmed its effectiveness for attractiveness estimation, we considered that it is necessary to introduce image features that evaluate the composition of ingredients for more accurate estimation, because they should significantly affect the attractiveness of food photography. Thus, we analyzed how the attractiveness is affected by understanding the composition of food ingredients through subjective experiments. We also investigated how it affects the performance of our method in the estimation accuracy, and studied the image features for attractiveness estimation. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | food photography / attractiveness / image features / regression analysis / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 117, no. 217, MVE2017-22, pp. 43-48, Sept. 2017. | |
| Paper # | MVE2017-22 | |
| Date of Issue | 2017-09-14 (MVE) | |
| ISSN | Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | MVE2017-22 |
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| Conference Information | |
| Committee | MVE |
| Conference Date | 2017-09-21 - 2017-09-22 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Chiba Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | MVE |
| Conference Code | 2017-09-MVE |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Quantitative analysis on image features for the estimation of the attractiveness of food photography |
| Sub Title (in English) | How the composition of ingredients affects the attractiveness |
| Keyword(1) | food photography |
| Keyword(2) | attractiveness |
| Keyword(3) | image features |
| Keyword(4) | regression analysis |
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| 1st Author's Name | Tatsumi Hattori |
| 1st Author's Affiliation | Chukyo University (Chukyo Univ.) |
| 2nd Author's Name | Keisuke Doman |
| 2nd Author's Affiliation | Chukyo University (Chukyo Univ.) |
| 3rd Author's Name | Ichiro Ide |
| 3rd Author's Affiliation | Nagoya University (Nagoya Univ.) |
| 4th Author's Name | Yoshito Mekada |
| 4th Author's Affiliation | Chukyo University (Chukyo Univ.) |
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| Speaker | Author-1 |
| Date Time | 2017-09-22 10:50:00 |
| Presentation Time | 30 minutes |
| Registration for | MVE |
| Paper # | MVE2017-22 |
| Volume (vol) | vol.117 |
| Number (no) | no.217 |
| Page | pp.43-48 |
| #Pages | 6 |
| Date of Issue | 2017-09-14 (MVE) |
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