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@article{ART003028388},
author={Hyun-Sik Ham and Sae Jun Ko},
title={A Study on Non-Contact Care Robot System through Deep Learning},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2023},
volume={28},
number={12},
pages={33-40},
doi={10.9708/jksci.2023.28.12.033}

TY - JOUR
AU - Hyun-Sik Ham
AU - Sae Jun Ko
TI - A Study on Non-Contact Care Robot System through Deep Learning
JO - Journal of The Korea Society of Computer and Information
PY - 2023
VL - 28
IS - 12
PB - The Korean Society Of Computer And Information
SP - 33
EP - 40
SN - 1598-849X
AB - As South Korea enters the realm of an super-aging society, the demand for elderly welfare services has been steadily rising. However, the current shortage of welfare personnel has emerged as a social issue. To address this challenge, there is active research underway on elderly care robots designed to mitigate the social isolation of the elderly and provide emergency contact capabilities in critical situations. Nonetheless, these functionalities require direct user contact, which represents a limitation of conventional elderly care robots. In this paper, we propose a solution to overcome these challenges by introducing a care robot system capable of interacting with users without the need for direct physical contact. This system leverages commercialized elderly care robots and cameras. We have equipped the care robot with an edge device that incorporates facial expression recognition and action recognition models. The models were trained and validated using public available data. Experimental results demonstrate high accuracy rates, with facial expression recognition achieving 96.5% accuracy and action recognition reaching 90.9%. Furthermore, the inference times for these processes are 50ms and 350ms, respectively. These findings affirm that our proposed system offers efficient and accurate facial and action recognition, enabling seamless interaction even in non-contact situations.
KW - Action Recognition;Care Robot;Deep Learning;Edge Device;Face Detection;Facial Expression Recognition
DO - 10.9708/jksci.2023.28.12.033
ER -

Hyun-Sik Ham and Sae Jun Ko. (2023). A Study on Non-Contact Care Robot System through Deep Learning. Journal of The Korea Society of Computer and Information, 28(12), 33-40.

Hyun-Sik Ham and Sae Jun Ko. 2023, "A Study on Non-Contact Care Robot System through Deep Learning", Journal of The Korea Society of Computer and Information, vol.28, no.12 pp.33-40. Available from: doi:10.9708/jksci.2023.28.12.033

Hyun-Sik Ham, Sae Jun Ko "A Study on Non-Contact Care Robot System through Deep Learning" Journal of The Korea Society of Computer and Information 28.12 pp.33-40 (2023) : 33.

Hyun-Sik Ham, Sae Jun Ko. A Study on Non-Contact Care Robot System through Deep Learning. 2023; 28(12), 33-40. Available from: doi:10.9708/jksci.2023.28.12.033

Hyun-Sik Ham and Sae Jun Ko. "A Study on Non-Contact Care Robot System through Deep Learning" Journal of The Korea Society of Computer and Information 28, no.12 (2023) : 33-40.doi: 10.9708/jksci.2023.28.12.033

Hyun-Sik Ham; Sae Jun Ko. A Study on Non-Contact Care Robot System through Deep Learning. Journal of The Korea Society of Computer and Information, 28(12), 33-40. doi: 10.9708/jksci.2023.28.12.033

Hyun-Sik Ham; Sae Jun Ko. A Study on Non-Contact Care Robot System through Deep Learning. Journal of The Korea Society of Computer and Information. 2023; 28(12) 33-40. doi: 10.9708/jksci.2023.28.12.033

Hyun-Sik Ham, Sae Jun Ko. A Study on Non-Contact Care Robot System through Deep Learning. 2023; 28(12), 33-40. Available from: doi:10.9708/jksci.2023.28.12.033

Hyun-Sik Ham and Sae Jun Ko. "A Study on Non-Contact Care Robot System through Deep Learning" Journal of The Korea Society of Computer and Information 28, no.12 (2023) : 33-40.doi: 10.9708/jksci.2023.28.12.033