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Development of a vision-based feature extraction for food intake estimation for a robotic assistive eating device

机译:一种基于视觉的基于视觉特征提取的机器人辅助饮食设备的特征提取

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Our research aims at making a mock-up of a multi grip tool for a robotic assistive device and a camera system which enable frail elderly to live more independently and to keep track of their food intake. In this research the development of a vision-based feature extraction for food intake report for a robotic assistive eating device is introduced. The proposed vision system is composed by a RGB-D camera and the eating aid device Bestic. In this paper, the authors proposed an algorithm for estimating the amount of intake food (e.g. candies) after the end of the meal. The proposed vision-based feature extraction was designed and implemented in order to take pictures of the plate during the meal as well as estimate the amount of intake food. A set experiments were carried out in order to verify the performance of the proposed vision system while estimating the amount of intake food with different amount of multicoloured candies as well as different light conditions. Based on the experimental results, we could verify the system performance is not affected by the amount of candies as well as the light conditions.
机译:我们的研究旨在为机器人辅助装置和一个相机系统进行多重抓地工具,使弱老年能够更独立地活下来,并跟踪他们的食物摄入量。在这项研究中,介绍了用于机器人辅助饮食设备的食物摄入报告的基于视觉的特征提取的发展。所提出的视觉系统由RGB-D相机和饮食辅助装置兼容。在本文中,作者提出了一种估算膳食结束后进气食物(例如糖果)的算法。设计和实施了基于视觉的基于视觉的特征提取,以便在膳食期间拍摄板的照片,以及估计进气量的量。进行了一个设定的实验,以验证所提出的视觉系统的性能,同时估计具有不同数量的多色糖果以及不同的光线条件的摄入食物的量。基于实验结果,我们可以验证系统性能不受糖果量以及光线的影响。

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