Facial Emotion Detection for Thai Elderly People using YOLOv7
Conference proceedings article
Authors/Editors
Strategic Research Themes
Publication Details
Author list: Thanapong Khajontantichaikun, Saichon Jaiyen, Siam Yamsaengsung, Pornchai Mongkolnam, and Thanitsorn Chirapornchai
Publication year: 2023
Title of series: -
Number in series: -
Volume number: -
Start page: 1
End page: 4
Number of pages: 4
Languages: English-United States (EN-US)
Abstract
Currently, many countries around the world are moving towards becoming an aging society. The mental health of the elderly is one of the key challenges in an aging society. In this research, the use of YOLOv7 for facial emotion detection in Thai elderly is examined. In the experiments, the performance of YOLOv7 is compared to Faster R-CNN and SSD. All models are trained and tested with a facial dataset of Thai elderly people. From the experimental result, YOLOv7 achieved the best performance among the compared models with the mean average precision of 0.95 while Faster R-CNN and SSD has the mean average precision of 0.86 and 0.84, respectively.
Keywords
Artificial Intelligence, Elderly, Facial Emotion Detection, YOLOv7