Real-time infrared target detection based on center points

A real-time target detection method based on center points is proposed for infrared imaging systems equipped with CPUs. Following the lightweight design principles, a backbone with low computational cost is first introduced for feature extraction. Correspondingly, an efficient feature fusion module is designed to exploit spatial and contextual information extracted from multi-stages. In addition, an auxiliary background suppression module is proposed to predict foreground regions to enhance the feature representation. Finally, a simple detection head predicts the target center point and its associated properties. Evaluations on the infrared aerial target dataset show that our proposed method achieves 90. 24% mAP at a speed of 21. 69 ms per frame on the CPU. It surpasses the state-of-the-art Tiny-YOLOv3 by 10. 16% mAP with only 21% FLOPs and 11% parameters while also runs 10. 02 ms faster. The results demonstrate its great potential for real-time infrared applications.