NDLI: Food Search Based on User Feedback to Assist Image-based Food Recording Systems

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Food Search Based on User Feedback to Assist Image-based Food Recording Systems

Content Provider	ACM Digital Library
Author	Horiguchi, Shota Maeda, Kazuki Kubota, Masanori Aizawa, Kiyoharu Amano, Sosuke Ogawa, Makoto
Abstract	Food diaries or diet journals are thought to be effective for improving the dietary lives of users. One important challenge in this field involves assisting users in recording their daily food intake. In recent years, food image recognition has attracted a considerable amount of research interest as a new technology to help record users 'food intake. However, since there are so many types of food, and it is unrealistic to expect a system to recognize all foods. In this paper, we propose an optimal combination of image recognition and interactive search in order to record users 'intake of food. The image recognition generates a list of candidate names for a given food picture. The user chooses the closest name to the meal, which triggers an associative food search based on food contents, such as ingredients. We show the proposed system is efficient to assist users maintain food journals.
Starting Page	71
Ending Page	75
Page Count	5
File Format	PDF
ISBN	9781450345200
DOI	10.1145/2986035.2986037
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-10-16
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Image recognition Associative search Food journal
Content Type	Text
Resource Type	Article

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