电子科技2024，Vol.37Issue(8)：1-7,7.DOI:10.16180/j.cnki.issn1007-7820.2024.08.001
基于雷达和视频融合的目标检测
Research on Object Detection Based on Radar and Video Fusion
摘要
Abstract
The object detection based on video has the problem of poor recognition effect in bad weather,so it is necessary to make up for video defects and improve the robustness of detection framework.In view of this problem,this study designs an object detection framework based on radar and video fusion.YOLOv5(You Only Look Once version 5)network is used to obtain image feature map and image detection frame,density-based clustering is used to obtain radar detection frame,and radar data is encoded to get object detection results based on radar information.Finally,the detection boxes of the two are superimposed to obtain a new ROI(Region of Interest),and the classifi-cation vector after fusion radar information is obtained,which improves the detection accuracy in extreme weather.The experimental results show that the mAP(mean Average Precision)of the framework reaches 60.07%,and the parameter number is only 7.64×106,which indicates that the framework has the characteristics of lightweight,fast computing speed and high robustness,and can be widely used in embedded and mobile platforms.关键词
传感器融合/雷达信号处理/雷达特征图提取/DBSCAN/卡尔曼滤波/目标检测/YOLOv5/R-CNNKey words
sensor fusion/radar signal processing/radar feature map extraction/DBSCAN/Kalman filter/ob-ject detection/YOLOv5/R-CNN分类
信息技术与安全科学引用本文复制引用
朱勇,黄永明,何幸..基于雷达和视频融合的目标检测[J].电子科技,2024,37(8):1-7,7.基金项目
江苏省重点研发计划(BE2022154)Key R&D Program of Jiangsu(BE2022154) （BE2022154）
