Infrared Face Detection Based on Data Enhancement and Its Application
Yuquan Zhou, Weijing He, Guodong Xie, Xin Liu, Zhendong Guo · 2023
With the rise of artificial intelligence, face recognition technology is also developing rapidly. At present, most face recognition methods are based on visible spectrum images, but the complex background environment, lighting conditions and diverse facial expressions hinder the progress of face recognition technology. In order to solve the above problems, this paper proposes an infrared face recognition algorithm based on the YOLOv5 model. In the data processing stage, this paper expands the sample data set using data enhancement techniques, and then trains it based on the YOLOv5 model. Finally, it is tested on infrared face images. The experimental results show that infrared faces can be recognized quickly and correctly by this algorithm.