|国家科技期刊平台
首页|期刊导航|火力与指挥控制|融合点云增强的多传感器三维目标检测方法

融合点云增强的多传感器三维目标检测方法OA北大核心CSTPCD

Multi-sensor 3D Target Detection Method with Fusion of Point Cloud Enhancement

中文摘要英文摘要

三维目标检测是自动驾驶环境感知中不可缺少的功能模块.相机传感器丰富的图像纹理信息可以弥补激光雷达点云的稀疏问题,提出一种即插即用的RI-Fusion模块实现激光雷达与相机的有效融合.通过球面坐标变换将点云转换为紧凑的范围视图表示,基于注意力机制将距离图像与相应的相机图像进行集成,将原始距离图像与融合特征相连接以保留点云的信息,并将融合结果投影到空间点云中.特征增强后的点云可以输入到基于激光雷达的三维目标检测器中.在KITTI三维目标检测基准上进行实验,结果表明,提出的融合方法能够显著增强多个基于激光雷达的三维目标检测器,且针对行人与骑行者等小目标可以获得更高的检测精度.

Three dimensional object detection is an indispensable function module in automatic driving environment perception.The rich image texture information of camera sensor can make up for the sparse problem of laser radar point cloud.A plug and play RI Fusion module is proposed to achieve the effective fusion of lidar and camera.The point cloud is converted into a compact range view representation through spherical coordinate transformation,the distance images are integrated with the corresponding camera images based on the attention mechanism,the original distance images are connected with the fusion features to retain the information of the point cloud,and the fusion results are projected into the spatial point cloud.The point cloud after feature enhancement can be input into the 3D target detector based on lidar.The experiments are carried out on KITTI 3D target detection benchmark,the results show that the proposed fusion method can significantly enhance multiple 3D target detectors based on lidar,and can achieve higher detection accuracy for small targets such as pedestrians and cyclists,etc.

王昕灿;郭志阳;赫钰涛;张迁

江苏航运职业技术学院交通工程学院,江苏 南通 226010江苏航运职业技术学院交通工程学院,江苏 南通 226010||上海理工大学光电信息与计算机工程学院,上海 200093上海理工大学光电信息与计算机工程学院,上海 200093||南京开放大学信息与机电学院,南京 210005

电子信息工程

三维目标检测多传感器融合点云

3D object detectionmulti sensorfusionpoint cloud

《火力与指挥控制》 2024 (006)

122-127,134 / 7

国家自然科学青年基金(62206114);江苏省高校自然科学面上项目(22KJB580003);江苏省高校青蓝工程基金;南通市社会民生科技计划基金资助项目(MS2023017)

10.3969/j.issn.1002-0640.2024.06.017

评论