MT-Diet: Automated smartphone based diet assessment with infrared images

Junghyo Lee, Ayan Banerjee, S. Gupta
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引用次数: 17

Abstract

In this paper, we propose MT-Diet, a smartphone-based automated diet monitoring system that interfaces a thermal camera with a smartphone and identifies types of food consumed at the click of a button. The system uses thermal maps of a food plate to increase accuracy of segmentation and extraction of food parts, and combines thermal and visual images to improve accuracy in the detection of cooked food. Test results on 80 different types of cooked food show that MT-Diet can isolate food parts with an accuracy of 97.5% and determine the type of food with an accuracy of 88.93%, which is a significant improvement (nearly 25%) over the state-of-the-art.
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MT-Diet:自动基于智能手机的饮食评估与红外图像
在本文中,我们提出了MT-Diet,这是一种基于智能手机的自动饮食监测系统,它将热像仪与智能手机连接在一起,只需点击一个按钮就能识别所消耗的食物类型。该系统使用食物板的热图来提高分割和提取食物部分的准确性,并结合热图像和视觉图像来提高熟食检测的准确性。对80种不同类型熟食的测试结果表明,MT-Diet可以以97.5%的准确率分离食物部位,并以88.93%的准确率确定食物类型,这是一个显着的进步(近25%)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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Leveraging proximity sensing to mine the behavior of museum visitors PanoVC: Pervasive telepresence using mobile phones Smart cities: Intelligent environments and dumb people? Panel summary MT-Diet: Automated smartphone based diet assessment with infrared images SECC: Simultaneous extraction of context and community from pervasive signals
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