针对车载激光雷达(light detection and ranging,LiDAR)点云数据的不完整性问题,提出一种车载LiDAR点云数据分割以及基于分割后点云数据的半自动化建模方法。首先对点云数据进行标准格式转换及稀化;然后以不同地物的属性和几何特征为分...针对车载激光雷达(light detection and ranging,LiDAR)点云数据的不完整性问题,提出一种车载LiDAR点云数据分割以及基于分割后点云数据的半自动化建模方法。首先对点云数据进行标准格式转换及稀化;然后以不同地物的属性和几何特征为分割条件,分别建立道路、建筑物、树和路灯等附属设施的三维模型,并利用车载以及航空图像的纹理信息辅助建筑物的立面和顶面三维建模;最后以真实街景为实验区,基于拓普康IP-S2车载LiDAR点云数据,完成该街景的分割与建模。实验结果表明,该文提出的点云数据分割与街景地物重建方法比较简单,可实现道路和建筑物的半自动化分割;利用成熟的建模软件和方法,实现了建模的完整性和较强的可靠性。展开更多
This paper proposes an automatic model-based viewpoint planning method, which can achieve high precision and high efficiency for freeform surfaces inspection using plane structured light scanners. The surface model is...This paper proposes an automatic model-based viewpoint planning method, which can achieve high precision and high efficiency for freeform surfaces inspection using plane structured light scanners. The surface model is utilized in stereolithography format, which is widely used as an industrial standard. The proposed method consists of 4 steps： topology reconstruction, mesh refinement, scan direction determination and viewpoint generation. In the first step, the topology structure of the surface model is reconstructed according to a designed data structure, based on which a neighborhood search algorithm is developed. In the second step, big facets in the surface model are segmented into several small ones, which are suitable for viewpoint planning. In the third step, an initial scan region of a viewpoint is grouped by the neighborhood search algorithm combining with total area and normal vector restrictions. Accordingly, the scan direction is determined by the normal vectors of facets in the initial scan region. In the fourth step, the position, the orientation, and the final scan region of the viewpoint are determined by 4 scan constraints, i.e., field of view, working distance range, view angle and overlap. Experimental results verify the effectiveness and advantages of the proposed method.展开更多
文摘针对车载激光雷达(light detection and ranging,LiDAR)点云数据的不完整性问题,提出一种车载LiDAR点云数据分割以及基于分割后点云数据的半自动化建模方法。首先对点云数据进行标准格式转换及稀化;然后以不同地物的属性和几何特征为分割条件,分别建立道路、建筑物、树和路灯等附属设施的三维模型,并利用车载以及航空图像的纹理信息辅助建筑物的立面和顶面三维建模;最后以真实街景为实验区,基于拓普康IP-S2车载LiDAR点云数据,完成该街景的分割与建模。实验结果表明,该文提出的点云数据分割与街景地物重建方法比较简单,可实现道路和建筑物的半自动化分割;利用成熟的建模软件和方法,实现了建模的完整性和较强的可靠性。
文摘This paper proposes an automatic model-based viewpoint planning method, which can achieve high precision and high efficiency for freeform surfaces inspection using plane structured light scanners. The surface model is utilized in stereolithography format, which is widely used as an industrial standard. The proposed method consists of 4 steps： topology reconstruction, mesh refinement, scan direction determination and viewpoint generation. In the first step, the topology structure of the surface model is reconstructed according to a designed data structure, based on which a neighborhood search algorithm is developed. In the second step, big facets in the surface model are segmented into several small ones, which are suitable for viewpoint planning. In the third step, an initial scan region of a viewpoint is grouped by the neighborhood search algorithm combining with total area and normal vector restrictions. Accordingly, the scan direction is determined by the normal vectors of facets in the initial scan region. In the fourth step, the position, the orientation, and the final scan region of the viewpoint are determined by 4 scan constraints, i.e., field of view, working distance range, view angle and overlap. Experimental results verify the effectiveness and advantages of the proposed method.
