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Food Volume Estimation in a Mobile Phone Based Dietary Assessment System

机译:基于手机饮食评估系统的食物体积估计

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There is now convincing evidence that poor diet, in combination with physical inactivity are key determinants of an individual's risk of developing chronic diseases, such as obesity, cancer, cardiovascular disease or diabetes. Assessing what people eat is fundamental to establishing the link between diet and disease. Food records are considered the best approach for assessing energy intake. However, this method requires literate and highly motivated subjects and adolescents and young adults are the least likely to undertake food records. The ready access of the majority of the population to mobile phones has opened up new opportunities for dietary assessment. In such systems, the camera in the mobile phone is used for capturing images of food consumed and these images are then processed to automatically estimate the nutritional content of the food. A vital step in this process is the estimation of the volume of the food in the image. In this paper we propose a food volume estimation approach which requires only a pair of stereo images to be captured. Our experimental results show that the proposed approach can provide an accurate estimate of the volume of typical food items in a passive manner without the need for manual fitting of 3D models to the food items.
机译:现在有令人信服的证据表明,不良的饮食习惯,与体力活动相结合是发展的慢性疾病,如肥胖,癌症,心血管疾病或糖尿病的个体风险的主要决定因素。评估人吃什么是建立饮食与疾病之间的联系的基础。食品记录被认为是评估能量摄入的最佳方法。然而,这种方法需要文化和高度激发科目和青少年和年轻的成年人是最有可能承担食品的记录。多数民众手机的随时访问开辟了新的机会进行膳食营养评价。在这种系统中,在移动电话相机被用于捕获消耗的食物图像和这些图像然后被处理以自动估计食物的营养成分。在这个过程中一个重要步骤是将食物的图像中的体积的估计。在本文中,我们提出一种只需要对立体图像被捕获的食物量估计方法。我们的实验结果表明,该方法可以提供以被动方式典型的食品的体积的精确估计,而无需3D模型的拟合手册的食品。

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