1) Point cloud curvature 点云曲率2) curves on point cloud 点云曲线 例句>> 3) point cloud surface 点云曲面 1. Compounded geometry image representation of point cloud surfaces and its application; 点云曲面的复合几何图像表示及其应用 更多例句>> ...
Curvature Computation 曲率计算 Curvature is a second-order derivative (二阶导), but triangles are flat. Rusinkiewicz's Method Acquiring Point Clouds LIDAR Infrared Stereo 圈状点云/条形点云 (雷达扫描) Simple to understand Compact to store Generally easy to build algorithms Sampling point cloud from...
The results of the point cloud alignment experiments show that the response time of the algorithm is less than 5s in the case where the curvature features of point cloud are obvious. And the alignment error can be reduced to 1% of the pre-alignment error. Therefore, the algorithm is an ...
However, this method assumes that the target shape is a smooth curve whose tangent and curvature information can easily be evaluated or estimated accurately, thus it is not applicable to a target point defined by a point cloud because of the difficulty ...
(3)Curvature Sensitivity:坐标很难描述三维点云的局部形状。RepSurf应该能够直观地突出显示边缘和局部形状 3. Triangular RepSurf 和定义2d曲线类似,定义一个3d切面也使用法向量v和一个点: 定义上述切面的位置为: 这里的法向量是使用叉积得到,也就是找两个相邻点得到两组向量,再将这两组向量叉积得到法向量。但是...
Considering the diversity of point cloud features, the simplification effects of traditional point cloud simplification algorithms (such as curvature, random and isometry simplification algorithms) are poor. To overcome these drawbacks, a point cloud simplification method based on adaptive curvature entropy ...
Point cloud will then draw in object local space. i.e. point cloud will be transformed in the same way as container object. The best is to use “Empty” object type as containers. PCV does not store loaded points in blend file because there is no suitable data type available. only PCV...
We present a novel and efficient method, called squared distance minimization (SDM), for computing a planar B-spline curve, closed or open, to approximate a target shape defined by a point cloud, that is, a set of unorganized, possibly noisy data points. We show that SDM signific...
We present an efficient and robust method for extracting curvature information, sharp features, and normal directions of a piecewise smooth surface from its point cloud sampling in a unified framework. Our method is integral in nature and uses convolved covariance matrices of Voronoi cells of the po...
The function of point feature histogram (PFH) is to encode the K-neighborhood geometric characteristics of points by summarizing the average curvature around points10. It is invariant to the corresponding surface of point cloud. PFH is robust under different sampling densities or noise in the neighb...