红外与毫米波学报2025，Vol.44Issue(5)：790-800,11.DOI:10.11972/j.issn.1001-9014.2025.05.017
YOLO-Fastest-IR:面向红外热像仪的超轻量级热红外人脸检测网络
YOLO-Fastest-IR:Ultra-lightweight thermal infrared face detection method for infrared thermal camera
摘要
Abstract
This paper presents a high-speed and robust dual-band infrared thermal camera based on an ARM CPU.The system consists of a low-resolution long-wavelength infrared detector,a digital temperature and humid-ity sensor,and a CMOS sensor.In view of the significant contrast between face and background in thermal infra-red images,this paper explores a suitable accuracy-latency tradeoff for thermal face detection and proposes a tiny,lightweight detector named YOLO-Fastest-IR.Four YOLO-Fastest-IR models(IR0 to IR3)with different scales are designed based on YOLO-Fastest.To train and evaluate these lightweight models,a multi-user low-resolution thermal face database(RGBT-MLTF)was collected,and the four networks were trained.Experiments demon-strate that the lightweight convolutional neural network performs well in thermal infrared face detection tasks.The proposed algorithm outperforms existing face detection methods in both positioning accuracy and speed,making it more suitable for deployment on mobile platforms or embedded devices.After obtaining the region of interest(ROI)in the infrared(IR)image,the RGB camera is guided by the thermal infrared face detection results to achieve fine positioning of the RGB face.Experimental results show that YOLO-Fastest-IR achieves a frame rate of 92.9 FPS on a Raspberry Pi 4B and successfully detects 97.4%of faces in the RGBT-MLTF test set.Ultimate-ly,an infrared temperature measurement system with low cost,strong robustness,and high real-time perfor-mance was integrated,achieving a temperature measurement accuracy of 0.3℃.关键词
人工智能/热红外人脸检测/超轻量级网络/热成像测温相机/YOLO-Fastest-IRKey words
artificial intelligence/infrared face detection/ultra-lightweight network/infrared thermal camera/YOLO-Fastest-IR分类
信息技术与安全科学引用本文复制引用
李希才,朱嘉禾,董鹏翔,王元庆..YOLO-Fastest-IR:面向红外热像仪的超轻量级热红外人脸检测网络[J].红外与毫米波学报,2025,44(5):790-800,11.基金项目
Supported by the Fundamental Research Funds for the Central Universities(2024300443) （2024300443）
the Natural Science Foundation of Jiangsu Province(BK20241224). （BK20241224）
