红外技术2024，Vol.46Issue(9)：1043-1050,8.
融合视觉显著性的红外航拍行人检测
Aerial Infrared Pedestrian Detection with Saliency Map Fusion
摘要
Abstract
Object detection is a fundamental task in computer vision.Drones equipped with infrared cameras facilitate nighttime reconnaissance and surveillance.To realize small target detection,slight texture information,weak contrast in infrared aerial photography scenes,limited accuracy of traditional algorithms,and heavy dependence on computing power and power consumption in infrared object detection,a pedestrian detection method for infrared aerial photography scenes that integrates salient images is proposed.First,we use U2-Net to generate saliency maps from the original thermal infrared images for image enhancement.Second,we analyze the impact of two fusion methods,pixel-level weighted fusion,and replacement of image channels as image-enhancement schemes.Finally,to improve the adaptability of the algorithm to the target scene,the prior boxes are reclustered.The experimental results show that pixel-level weighted fusion presents excellent results.This method improves the average accuracy of typical YOLOv3,YOLOv3-tiny,and YOLOv4-tiny algorithms by 6.5%,7.6%,and 6.2%,respectively,demonstrating the effectiveness of the designed fused visual saliency method.关键词
红外行人检测/图像增强/显著图/YOLOv4Key words
infrared pedestrian detection/salient map/image enhancement/YOLOv4分类
计算机与自动化引用本文复制引用
张兴平,邵延华,梅艳莹,张晓强,楚红雨..融合视觉显著性的红外航拍行人检测[J].红外技术,2024,46(9):1043-1050,8.基金项目
国家自然科学基金资助项目(61601382) （61601382）
四川省自然科学基金资助项目(2023NSFSC1388). （2023NSFSC1388）
