AR DeepCalorieCam V2:使用CNN和基于AR的实际尺寸估计进行食物卡路里估计

Ryosuke Tanno, Takumi Ege, Keiji Yanai
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引用次数: 16

摘要

在大多数情况下,估计的卡路里只是与估计的食物类别相关联,或者与每种食物类别的标准尺寸相比较,这些通常是由用户手动提供的。此外,在基于餐量估算卡路里的情况下,用户通常需要提前注册一个已知大小的参考对象,并使用注册的参考对象拍摄食物照片。在这个演示中,我们提出了一种基于CNN和增强现实(AR)的食物卡路里估计的新方法。通过使用Apple ARKit框架,我们可以通过获取现实世界上的坐标作为三维矢量来测量用餐区域的实际大小,我们实现了这个演示应用程序。因此,可以比之前直接测量用餐区域的方法更准确地计算出大小,提高了卡路里估算的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AR DeepCalorieCam V2: food calorie estimation with CNN and AR-based actual size estimation
In most of the cases, the estimated calories are just associated with the estimated food categories, or the relative size compared to the standard size of each food category which are usually provided by a user manually. In addition, in the case of calorie estimation based on the amount of meal, a user conventionally needs to register a size-known reference object in advance and to take a food photo with the registered reference object. In this demo, we propose a new approach for food calorie estimation with CNN and Augmented Reality (AR)-based actual size estimation. By using Apple ARKit framework, we can measure the actual size of the meal area by acquiring the coordinates on the real world as a three-dimensional vector, we implemented this demo app. As a result, it is possible to calculate the size more accurately than in the previous method by measuring the meal area directly, the calorie estimation accuracy has improved.
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