Facial expression recognition based on YOLOv9 improvement
Kun Meng, Jiarui Si, Tao Yang, Hong Tian · 2025
Facial expression recognition is an important application field in computer vision, by recognizing and analyzing the expressions on human faces, it can be widely used in many fields such as sentiment computing and security intelligent monitoring. Nowadays, the aging trend in China is very serious, and the issue of real-time monitoring of the safety of the left-behind elderly has become crucial. In this paper, RGS-YOLOv9, a facial expression recognition algorithm for improving yolov9, is proposed by replacing the original RepNCSPELAN4 module of yolov9 with RepNCSPELAN4_ UIB module and introducing SDI module as a connection. The experimental results show that mAP_0.5 on the Human Face Expression dataset improves by 3.3% and mAP_0.5:0.95 improves by 2.6%. This experiment provides new technical ideas for intelligent monitoring to improve the safety and security of the elderly.