Bruno Vieira, Resende Silva, Juan Cui
Department of Computer Science and Engineering, University of Nebraska-Lincoln, NE, USA.
J Health Med Inform. 2017;8(3). doi: 10.4172/2157-7420.1000272. Epub 2017 Jul 15.
Healthy diet with balanced nutrition is key to the prevention of life-threatening diseases such as obesity, cardiovascular disease, and cancer. Recent advances in smartphone and wearable sensor technologies have led to a proliferation of food monitoring applications based on automated food image processing and eating episode detection, with the goal to conquer drawbacks of the traditional manual food journaling that is time consuming, inaccurate, underreporting, and low adherent. In order to provide users feedback with nutritional information accompanied by insightful dietary advice, various techniques in light of the key computational learning principles have been explored. This survey presents a variety of methodologies and resources on this topic, along with unsolved problems, and closes with a perspective and boarder implications of this field.
营养均衡的健康饮食是预防肥胖、心血管疾病和癌症等危及生命疾病的关键。智能手机和可穿戴传感器技术的最新进展导致了基于自动食物图像处理和饮食事件检测的食物监测应用的激增，目的是克服传统手动食物记录的缺点，即耗时、不准确、漏报和依从性低。为了向用户提供带有深刻饮食建议的营养信息反馈，人们探索了基于关键计算学习原理的各种技术。本综述介绍了关于这一主题的各种方法和资源，以及未解决的问题，并以该领域的一个观点和更广泛的影响作为结尾。
