现代信息科技2025，Vol.9Issue(5)：56-61,6.DOI:10.19850/j.cnki.2096-4706.2025.05.010
基于PointPillars的多模态融合三维目标检测方法
Multi-modal Fusion 3D Object Detection Method Based on PointPillars
摘要
Abstract
The sparsity and disorder of point cloud data lead to the problems of missed detection and false detection in the detection of distant and small objects.Therefore,this paper proposes a multi-modal fusion 3D object detection algorithm based on the PointPillars algorithm.The algorithm designs a multi-modal feature fusion pillar encoding module,which can fuse point cloud features and image features,thereby enhancing the semantic information of features and improving the detection accuracy of distant and small objects.The experimental results on the KITTI dataset show that compared with the baseline model,the 3D average detection accuracy of the vehicle,pedestrian and cyclist categories is improved by 3.28%,2.88%and 1.62%,respectively.The results show that the proposed multi-modal fusion 3D object detection method based on PointPillars can effectively reduce the false detection and missed detection of distant and small objects.关键词
多模态融合/三维目标检测/柱体化编码/PointPillarsKey words
multi-modal fusion/3D Object Detection/pillar encoding/PointPillars分类
信息技术与安全科学引用本文复制引用
王睿智,张虹..基于PointPillars的多模态融合三维目标检测方法[J].现代信息科技,2025,9(5):56-61,6.基金项目
太原师范学院研究生教育创新项目(SYYJSYC-2395) （SYYJSYC-2395）
