用智能手机和餐具估算食物重量

E. Hippocrate, H. Suwa, Yutaka Arakawa, K. Yasumoto
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引用次数: 24

摘要

在物联网(IoT)时代,医疗保健系统是备受研究人员关注的领域之一。手机、手表或鞋子等日常生活用品与传感器相结合,形成监测和管理人们健康的卫生系统。近年来,利用食物摄影和相关的图像处理技术来评估食物的营养成分以控制卡路里的摄入已经成为一些研究的重点。然而,这种基于图像的饮食评估工具的关键问题之一是图像中食物部分的大小和重量的准确性和一致性估计。在本文中,我们提出了一个系统,使用进食工具(餐具),如勺子,叉子或筷子来测量食物在图片中的重量,以估计食物的卡路里含量,用于饮食评估和肥胖预防。我们的系统只要求用户从顶部拍摄一张照片,照片中有餐具。利用多种图像处理技术和图像的EXIF元数据,系统自动估计出食品容器的直径和高度,并推导出食品体积。然后,给定食物类型,系统将容器直径、高度和食物类型的信息结合起来,提供图像中食物的重量。实验结果表明,该系统对测试食品图像的权重估计平均相对错误率为6.87%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Food Weight Estimation using Smartphone and Cutlery
In this era of Internet of Things (IoT), the healthcare system is one of the fields that has received a lot of attention from researchers. Daily-life things and objects such as mobile phones, watches, or shoes are coupled with sensors to make health systems for monitoring, and managing people heath. Recently, some methods have been focused on using food photography and associated image-processing techniques to assess food nutrients to control calorie intake. However, one of the critical issues in such image-based dietary assessment tools is the accuracy and consistent estimation of the sizes and weights of the food portion in the image. In this paper, we propose a system that uses eating tools (cutlery) such as spoon, fork or chopsticks to measure the weight of a food in a picture, in order to estimate the calorie content of that food, for diet assessment and obesity prevention. Our system requires the user to take only a single image from the top with the cutlery in the picture. Using several image processing techniques and the EXIF metadata of the image, the system automatically estimates the diameter and the height of the food container and derives the food volume. Then, given the food type, the system combines the information about the container diameter, height and the food type to provide the weight of the food in the image. Our experiments show tenable results from the system which achieved an average relative error rate of 6.87% for the weight estimation, over the testing food images.
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