A scheme for an automatic road surface modeling from a noisy point cloud is presented. The normal vectors of the point cloud are estimated by distance-weighted fitting of local plane. Then, an automatic recognition of...A scheme for an automatic road surface modeling from a noisy point cloud is presented. The normal vectors of the point cloud are estimated by distance-weighted fitting of local plane. Then, an automatic recognition of the road surface from noise is performed based on the fuzzy clustering of normal vectors, with which the mean value is calculated and the projecting plane of point cloud is created to obtain the geometric model accordingly. Based on fuzzy clustering of the intensity attributed to each point, different objects on the road surface are assigned different colors for representing abundant appearances. This unsupervised method is demonstrated in the experiment and shows great effectiveness in reconstructing and rendering better road surface.展开更多
点云的几何精度、反射强度信息对于多线激光雷达(light detection and ranging,LiDAR)的实际应用有着重要的意义。针对扫描几何条件对点云质量的影响,本文构建了扫描距离、入射角度与多线激光雷达信号衰减的模型关系,从理论上分析了扫...点云的几何精度、反射强度信息对于多线激光雷达(light detection and ranging,LiDAR)的实际应用有着重要的意义。针对扫描几何条件对点云质量的影响,本文构建了扫描距离、入射角度与多线激光雷达信号衰减的模型关系,从理论上分析了扫描距离、入射角度对点云几何精度、反射强度的影响,提出了一种基于平面拟合的点云质量评估方法。在5~50 m的扫描距离、0°~60°的扫描入射角情况下,对3种多线激光雷达进行了测试。实验结果表明,随着扫描距离和入射角度的增加,多线激光雷达的测距中误差逐渐增加,点云反射强度准确性逐渐降低。展开更多
基金Supported by the National Natural Science Foundation of China （No.40471089） and the Key Laboratory of Geo-informatics of State Bureau of Surveying and Mapping.
文摘A scheme for an automatic road surface modeling from a noisy point cloud is presented. The normal vectors of the point cloud are estimated by distance-weighted fitting of local plane. Then, an automatic recognition of the road surface from noise is performed based on the fuzzy clustering of normal vectors, with which the mean value is calculated and the projecting plane of point cloud is created to obtain the geometric model accordingly. Based on fuzzy clustering of the intensity attributed to each point, different objects on the road surface are assigned different colors for representing abundant appearances. This unsupervised method is demonstrated in the experiment and shows great effectiveness in reconstructing and rendering better road surface.
文摘点云的几何精度、反射强度信息对于多线激光雷达(light detection and ranging,LiDAR)的实际应用有着重要的意义。针对扫描几何条件对点云质量的影响,本文构建了扫描距离、入射角度与多线激光雷达信号衰减的模型关系,从理论上分析了扫描距离、入射角度对点云几何精度、反射强度的影响,提出了一种基于平面拟合的点云质量评估方法。在5~50 m的扫描距离、0°~60°的扫描入射角情况下,对3种多线激光雷达进行了测试。实验结果表明,随着扫描距离和入射角度的增加,多线激光雷达的测距中误差逐渐增加,点云反射强度准确性逐渐降低。
