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

来源：

Jang, Inhoon (inhuns@hknu.ac.kr); Ko, Kwangeun (kke0217@kitech.re.kr) | 2021年 / Institute of Control, Robotics and Systems卷 / 27期

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

页码：334 / 341

页数：7

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