Meal intention recognition system based on gaze direction estimation using deep learning for the user of meal assistant robot

被引:7
作者
Park H. [1 ,2 ]
Jang I. [3 ]
Ko K. [1 ]
机构
[1] Applied Robot R&D Department, Korea Institute of Industrial Technology
[2] Department of Computer Science & Engineering, Hanyang University
[3] Industry Academic Cooperation Foundation, Hankyong National University
关键词
Deep learning; Gaze-direction recognition; Human-robot interaction; Meal-assistant robot;
D O I
10.5302/J.ICROS.2021.21.0019
中图分类号
学科分类号
摘要
Care robots that provide dietary supplements to the elderly and the disabled should be able to intelligently interact with the users’ intention to eat in real-time and provide the food they want. To this end, based on deep learning, we have developed a user interface that facilitates the selection of food to be eaten according to six user gaze directions. A single-stage object-detection deep learning model has been implemented as a lightweight, single-stage object-detection deep learning model that can be installed on commercial tablets, and the accuracy of this model was 0.9857. © ICROS 2021.
引用
收藏
页码:334 / 341
页数:7
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