河北科技大学学报2026，Vol.47Issue(3)：229-236,8.DOI:10.7535/hbkd.2026yx03001
基于YOLOv5与RGB-D融合的交通锥桶识别与定位方法研究
Research on traffic cone recognition and localization method based on YOLOv5 and RGB-D fusion
摘要
Abstract
To meet the requirements of real-time traffic cone detection and three-dimensional localization in construction and testing scenarios involving traffic cones,and to alleviate false positives and missed detections under complex illumination and occlusion conditions,this paper proposed a traffic cone recognition and localization method based on YOLOv5 and RGB-D fusion.First,863 cone images featuring diverse lighting,viewing angles,and backgrounds were collected and annotated,and divided into training and validation sets in an 8∶2 ratio.Through data augmentation,hyperparameter tuning,and an early stopping strategy,the optimal model weights were obtained.Next,the trained model was deployed on an Intel RealSense D435 camera,achieving synchronized acquisition and spatial alignment of RGB and depth frames.Finally,depth information was extracted from the center region of the detection bounding box and combined with camera intrinsic parameters for back-projection to estimate 3D coordinates.Experimental results indicate that the proposed method has high detection accuracy(Precision≈99.8%,Recall≈99.6%,and mAP@0.5≈99.5%),with a processing speed of approximately 26 FPS(≈37 ms per frame),an average localization error of less than 5 cm.The method maintains stable performance under challenging conditions such as strong glare,shadows,and partial occlusion.This method integrates 2D detection and 3D localization of traffic cones,ensuring high detection accuracy while balancing real-time performance and localization precision.It can provide reference for traffic cone perception.关键词
计算机感知/交通锥桶检测/三维定位/深度估计/实时定位Key words
computer perception/traffic cone detection/3D localization/depth estimation/real-time positioning分类
信息技术与安全科学引用本文复制引用
李鹏,贾正楷,杨洪玖,刘猛..基于YOLOv5与RGB-D融合的交通锥桶识别与定位方法研究[J].河北科技大学学报,2026,47(3):229-236,8.基金项目
国家自然科学基金(62403350,62373269) （62403350,62373269）
