| Presentation | 2013-03-11 Ingredients Estimation in a Dish by Learning from a Large Number of Recipes with Images Hiroki MATSUNAGA, Satoshi YOKOI, Yasuhiro HAYASHI, Keisuke DOMAN, Ichiro IDE, Daisuke DEGUCHI, Hiroshi MURASE, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this report, we propose a method for estimating the ingredients contained in the dish in an input food image. Recently, the number of services that analyzes the preferences of an individual by recording daily meals, for improving of health, is increasing. Conventional works that try to realize such services, estimate the calorie from the name of the dish detected from the image. However, in practice, different ingredients may be used in the same kind of dishes, so only recognizing the type of a dish is insufficient. Therefore, we propose a method for estimating the ingredients in the dish in an input food image. Since the color and the shape features of an ingredient tend to appear in a dish, the proposed method extracts image feature from the food image and builds classifiers. As a result of an evaluation experiments, we confirmed that the performance of the classifier exceeds random classification. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Food image / ingredient detection / image feature |
| Paper # | IMQ2012-55,IE2012-159,MVE2012-116,WIT2012-65 |
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| Conference Information | |
| Committee | MVE |
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| Conference Date | 2013/3/4(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
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| Paper Information | |
| Registration To | Media Experience and Virtual Environment (MVE) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Ingredients Estimation in a Dish by Learning from a Large Number of Recipes with Images |
| Sub Title (in English) | |
| Keyword(1) | Food image |
| Keyword(2) | ingredient detection |
| Keyword(3) | image feature |
| 1st Author's Name | Hiroki MATSUNAGA |
| 1st Author's Affiliation | Faculty of Engineering, Nagoya University() |
| 2nd Author's Name | Satoshi YOKOI |
| 2nd Author's Affiliation | Graduate School of Information Science, Nagoya University |
| 3rd Author's Name | Yasuhiro HAYASHI |
| 3rd Author's Affiliation | Graduate School of Information Science, Nagoya University |
| 4th Author's Name | Keisuke DOMAN |
| 4th Author's Affiliation | School of Information Science & Technology, Chukyo University |
| 5th Author's Name | Ichiro IDE |
| 5th Author's Affiliation | Graduate School of Information Science, Nagoya University |
| 6th Author's Name | Daisuke DEGUCHI |
| 6th Author's Affiliation | Information and Communications Headquarters, Nagoya University |
| 7th Author's Name | Hiroshi MURASE |
| 7th Author's Affiliation | Graduate School of Information Science, Nagoya University |
| Date | 2013-03-11 |
| Paper # | IMQ2012-55,IE2012-159,MVE2012-116,WIT2012-65 |
| Volume (vol) | vol.112 |
| Number (no) | 474 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |