Background

Food object recognition systems present an attractive and useful research field since they enable objective measurements of eating activity. This feature is helpful and welcome in many dieting related instances, especially for managing health conditions or for analyzing eating patterns of research subjects.

Scope and approach

We evaluate current food object recognition systems that were implemented on a mobile device. The evaluation was provided by analysing each particular system through its food recognition process. The whole recognition process was divided into 6 distinct stages: image acquisition, image processing, image segmentation, feature extraction, image classification, and volume estimation.

Key findings and conclusions

Through the analysis, the authors provide a categorization of mobile food recognition systems: recorder systems, suggester systems, and clinical responders. Each group is aimed at a different scenario which helps to identify features a particular system should focus its development on.

中文翻译：

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使用移动设备识别食物对象：对当前实施系统的评估

背景

食品对象识别系统由于能够客观地测量饮食活动，因此呈现出有吸引力且有用的研究领域。在许多与节食有关的情况下，此功能非常有用，尤其是在管理健康状况或分析研究对象的饮食方式方面。

范围和方法

我们评估当前在移动设备上实现的食品对象识别系统。通过对每个特定系统的食品识别过程进行分析来提供评估。整个识别过程分为6个不同的阶段：图像获取，图像处理，图像分割，特征提取，图像分类和体积估计。

主要发现和结论

通过分析，作者提供了移动食品识别系统的分类：记录器系统，建议系统和临床响应者。每个小组针对的是不同的场景，这有助于确定特定系统应重点关注的功能。