{"title":"Food Search Based on User Feedback to Assist Image-based Food Recording Systems","authors":"Sosuke Amano, Shota Horiguchi, K. Aizawa, Kazuki Maeda, Masanori Kubota, Makoto Ogawa","doi":"10.1145/2986035.2986037","DOIUrl":null,"url":null,"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.","PeriodicalId":91925,"journal":{"name":"MADiMa'16 : proceedings of the 2nd International Workshop on Multimedia Assisted Dietary Management : October 16, 2016, Amsterdam, The Netherlands. International Workshop on Multimedia Assisted Dietary Management (2nd : 2016 : Amsterdam...","volume":"122 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2016-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"MADiMa'16 : proceedings of the 2nd International Workshop on Multimedia Assisted Dietary Management : October 16, 2016, Amsterdam, The Netherlands. International Workshop on Multimedia Assisted Dietary Management (2nd : 2016 : Amsterdam...","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2986035.2986037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
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.