可穿戴环境感知食物识别,用于卡路里监测

Geeta Shroff, A. Smailagic, D. Siewiorek
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引用次数: 63

摘要

我们提出DiaWear,一种新型的基于手机的辅助卡路里监测系统,以改善糖尿病患者和具有独特营养管理需求的个人的生活质量。我们的目标是使用移动可穿戴手机实现改进的日常半自动食物识别。DiaWear目前使用神经网络分类方案从捕获的图像中识别食物。使用传统的图像识别技术很难解释某些食物的变化和隐含性质。为了克服这些限制,我们引入了手机作为平台的作用,从用户和系统收集上下文信息,以获得更好的食物识别。
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Wearable context-aware food recognition for calorie monitoring
We propose DiaWear, a novel assistive mobile phone-based calorie monitoring system to improve the quality of life of diabetes patients and individuals with unique nutrition management needs. Our goal is to achieve improved daily semi-automatic food recognition using a mobile wearable cell phone. DiaWear currently uses a neural network classification scheme to identify food items from a captured image. It is difficult to account for the varying and implicit nature of certain foods using traditional image recognition techniques. To overcome these limitations, we introduce the role of the mobile phone as a platform to gather contextual information from the user and system in obtaining better food recognition.
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