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

Sosuke Amano, Shota Horiguchi, K. Aizawa, Kazuki Maeda, Masanori Kubota, Makoto Ogawa
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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.
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基于用户反馈的食物搜索辅助基于图像的食物记录系统
饮食日记或饮食日记被认为对改善用户的饮食生活很有效。这个领域的一个重要挑战是帮助用户记录他们每天的食物摄入量。近年来,食物图像识别作为一种帮助记录用户食物摄入量的新技术引起了相当多的研究兴趣。然而,由于食物种类繁多,期望一个系统识别所有食物是不现实的。在本文中,我们提出了一种图像识别和交互式搜索的最佳组合,以记录用户的食物摄入量。图像识别为给定的食物图片生成候选名称列表。用户选择与食物最接近的名字,这将触发基于食物内容(如配料)的关联食物搜索。我们展示了建议的系统是有效的,以帮助用户维护食品日志。
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