point-clouds

问题 I need to find the transformation and rotation difference between two 3d point clouds. For this I am looking at PCL, as it seems ideal. On clean test data I have Iterative closest point working, but giving strange results(although I may have implemented it incorrectly...) I have pcl::estimateRigidTransformation working, and it seems better, although I assume will deal worse with noisy data. My question is: The two clouds will be noisy, and although they should contain the same points, there

问题 I have a point cloud from kinect fusion and use Point Cloud Library to segment the ground plane(a x+b y+c*z+d=0) successfully(I got the a,b,c,d in pcl::ModelCoefficients of the ground plane). Now I need to transform the Cartesian coordinates to new Cartesian coordinates that makes the ground plane became the X-O-Y plane(0*x+0*y+z=0). I guess I can do it by this API(but I don't know how): http://docs.pointclouds.org/trunk/group__common.html#transformPointCloud My Answer : Look at this PCL api

问题 I am using the MayaVi Python library to plot 3d points, using the points3d class. The documentation specifies that the colour of each point is specified through a fourth argument, s : In addition, you can pass a fourth array s of the same shape as x, y, and z giving an associated scalar value for each point, or a function f(x, y, z) returning the scalar value. This scalar value can be used to modulate the color and the size of the points. This specifies a scalar value for each point, which

问题 I am trying to perform a segmentation task with PCL/ROS. I am using the dynamic configuration option in ROS as the number of inputs to my segmentation task is large and would like to study the influence of each param . There is no problem with my C++ source code, however when I try to run the launch file my file publisher is not able to find the PCD files. <launch> <!-- Start segmentation analysis --> <node pkg="segmentation_analysis" name="region_growing" type="region_growing" output="screen

问题 I have a 3D point cloud each with different color/values attribute attached to each vertex of XYZ points. The Raw data is in simple .txt / csv form in columns i.e x, y, z, V1, V2, V3 and a new line for next point I am trying to use .ply to make images. I want to create a 3D image such as: . What is the appropriate code in ply format to color each surface or vertex based on each of these values? I want to create multiple maps with the same shape but mapping different colors to the surface. 回答1

问题 I have a set of point cloud forming a plane in 3D, which I've obtained from RANSAC plane fitting. For some specific kind of analysis of the data I need to convert this to a 2D problem so that I can have all the z-values almost same. Suppose the equation of the plane is ax+by+cz+1=0. My question is that: How can I get the values of a,b,c from raw point cloud data? Will least square be the best approach or there is any way to obtain these values from RANSAC fitting? From some tutorials I got an

问题 I need to reconstruct a surface mesh of a terrain from a dense point cloud. Is it possible to generate polygonal meshes from point clouds in Meshlab v2016.12? 回答1: Yes you can!. The process of generating a mesh from a point cloud is called surface reconstruction. There are several surface reconstruction methods avaliable in meshlab. Go to Filters -> Remeshing, simplification and Reconstruction There you can select one of the many choices avaliable. To guide you a little: Delanuay

问题 I am working with a project that requires accessing point cloud data in the form of .ply files and converting them into numpy arrays for running a deep learning algorithm. When I try to access my .ply files from my directory, I get the error "ValueError: two properties with same name" The following is my code - import glob import numpy as np from plyfile import PlyData, PlyElement arr = np.array([]) for filepath in glob.iglob('/content/drive/My Drive/PLY Files/*.ply'): plyFile = PlyData.read

问题 I am working on a classification problem (object classification for autonomous vehicle). I use a dataset from KITTI which provide Lidar and camera Data and want to use both of this data to perform the task. 3D LIDAR data is projected onto the coordinatesystem of the RGB image resulting in a sparse LIDAR image : Each pixel is encoding using depth (distance to the point : sqrt(X² + Y²), scaling between 0 and 255). In order to obtain better results for my CNN, I need a dense lidar image, anyone

问题 For a project I am working on, I have successfully performed the SFM procedure on road image data, and have been able to generate a .ply file containing point cloud coordinates (X, Y, Z), RGB values, and normals (nx, ny, nz). Now, I am interested in calculating curvature values for each point from the data I have. I have come across Surface Curvature MATLAB Equivalent in Python, but the implementation is said to work only when X, Y, and Z are 2D arrays. Is Gaussian and Mean curvatures