体积热力学
卡路里
扫描仪
跟踪(教育)
过程(计算)
计算机科学
食物摄入量
估计
计算机视觉
人工智能
工程类
医学
操作系统
系统工程
内分泌学
内科学
物理
心理学
量子力学
教育学
作者
Sep Makhsous,Jack Gentsch,Joshua Rollins,Zachary Feingold,Alexander Mamishev
出处
期刊:International journal of engineering & technology
[Science Publishing Corporation]
日期:2018-12-03
卷期号:7 (4.38): 1368-1371
标识
DOI:10.14419/ijet.v7i4.38.27876
摘要
The prevalence of obesity, found in more than 38% of worldwide adults, is causing dietary measurements to become increasingly important. Most methods for tracking dietary intake utilize estimating the amount of food consumed to determine calories and nutritional content. Currently used methods of dietary tracking are either tedious or inaccurate. Our proposed method for dietary tracking is called DietSkan. It combines an off the shelf 3-Dimensional (3D) scanner, the Structure Sensor, with a smartphone application to produce a 3D reconstructed mesh scan of food items. The DietSkan process requires the desired food item to be scanned and exported for volume calculation. Then, using a 3D mesh manipulation tool, a 3D mesh, enclosing the consumed food, is constructed to obtain volume. The volume measurements achieved using the DietSkan algorithm average only 6% error and allow a user to track their dietary intake simply and effectively. The DietSkan system simplifies the estimation process and improves measurement accuracy when compared to current common practices. Â
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