point-clouds

Rectangle Detection in PCL

由 核能气质少年 提交于 2019-12-06 22:09:42
How do I perform rectangle-fitting in PCL? PCL allows RANSAC for a limited set of models (sphere, cylinder, etc) but not for rectangles. Is there a way to do rectangle-fitting with PCL's RANSAC or perhaps another PCL module? 来源： https://stackoverflow.com/questions/54100897/rectangle-detection-in-pcl

Point cloud XYZ format specification

由 守給你的承諾、 提交于 2019-12-06 19:48:36
问题 Is there an official specification for the XYZ format for point clouds? I've been searching all over and I didn't find it. I've seen that there are some files which line contains: points coordinates, (X Y Z for each point ) others contain coordinates plus colors, (X Y Z R G B for each point ) there are even others that have an "Intensity" parameter. I need to consider all the possibilities. 回答1: No, there is not an official specification about the .xyz format for point clouds. The .xyz format

Generate and export point cloud from Project Tango

由 放肆的年华 提交于 2019-12-06 15:25:39
After some weeks of waiting I finally have my Project Tango. My idea is to create an app that generates a point cloud of my room and exports this to .xyz data. I'll then use the .xyz file to show the point cloud in a browser! I started off by compiling and adjusting the point cloud example that's on Google's github. Right now I use the onXyzIjAvailable(TangoXyzIjData tangoXyzIjData) to get a frame of x y and z values; the points. I then save these frames in a PCLManager in the form of Vector3 . After I'm done scanning my room, I simple write all the Vector3 from the PCLManager to a .xyz file

Detecting set of planes from point cloud

由 回眸只為那壹抹淺笑 提交于 2019-12-06 04:56:00
I have a set of point cloud, and I would like to test if there is a corner in a 3D room. So I would like to discuss my approach and if there is a better approach or not in terms of speed, because I want to test it on mobile phones. I will try to use hough tranform to detect lines, then I will try to see if there are three lines that are intersecting and they make a two plane that are intersecting too. If the point cloud data comes from a depth sensor, then you have a relatively dense sampling of your walls. One thing I found that works well with depth sensors (e.g. Kinect or DepthSense) is a

generate a point cloud from a given depth image-matlab Computer Vision System Toolbox

由 限于喜欢 提交于 2019-12-06 04:34:17
I am a beginner in matlab, I have purchased Computer Vision System Toolbox. I have being given 400 of depth images (.PNG images). I would like to create a point cloud for each image. I looked at the documentation of Computer Vision System Toolbox, and there is an example of converting depth image to point cloud ( http://uk.mathworks.com/help/vision/ref/depthtopointcloud.html ): [xyzPoints,flippedDepthImage] = depthToPointCloud(depthImage,depthDevice) depthDevice = imaq.VideoDevice('kinect',2) but the thing that I don't understand is that it requires Kinect camera and connection . I am not

Checking point coordinates in PCLVisualizer

由 ≡放荡痞女 提交于 2019-12-05 21:56:32
How can I check specific point coordinates in PCLVisualizer? There are no information regarding this topic in help: | Help: ------- p, P : switch to a point-based representation w, W : switch to a wireframe-based representation (where available) s, S : switch to a surface-based representation (where available) j, J : take a .PNG snapshot of the current window view c, C : display current camera/window parameters f, F : fly to point mode e, E : exit the interactor q, Q : stop and call VTK's TerminateApp +/- : increment/decrement overall point size +/- [+ ALT] : zoom in/out g, G : display scale

PCL: Visualise a point cloud

由 假装没事ソ 提交于 2019-12-05 15:50:53
问题 I'm trying to visualise point cloud using PCL CloudViewer. The problem is that I'm quite new to C++ and I have found two tutorials first demonstrating the creation of PointCloud and second demonstration the visualisation of a PointCloud. However, I'm not able to combine these two tutorials. Here is what I come with: #include <iostream> #include <pcl/io/pcd_io.h> #include <pcl/point_types.h> #include <pcl/visualization/cloud_viewer.h> int main (int argc, char** argv) { pcl::PointCloud<pcl:

How do I interpolate a 2D gridded point cloud to a continuous area?

由 天涯浪子 提交于 2019-12-05 09:33:13
I have a 2 dimensional Numpy NDarray filled with floats between 0 and about 8. This 2 dimensional arrays size is (1000, 1600) and there are about 1400 values, (the points in the point cloud), the remaining values are None , so matplotlib does not plot these values. You can see the plotted table in the image below. What I'd like to have is, the None-values interpolated with the values next to it to have a gradientlike heatmap. This pointcloud represents the shape of a roof and I want to process this data to an image I can give into a neural network to detect the type of roof. The code I used

Set-to-Subset point cloud matching

由 做~自己de王妃 提交于 2019-12-05 04:08:52
问题 I have two point clouds, in 3d coordinates. One is a subset of the other, containing many less points. They are in the same scale. What i need to do is find the translation and rotation between the two. I have looked at Point cloud Library, "Iterative closest point", and Coherent Point Drift, but these matching approaches both seem to expect the two point sets to contain mostly the same points, not have one be a smaller, subset of the other. Can i use either of these, with adjustments? Or is

How to read .ply file using PCL

由 非 Y 不嫁゛ 提交于 2019-12-05 02:00:21
问题 I can read .pcd data using this program. #include <iostream> #include <pcl/io/pcd_io.h> #include <pcl/point_types.h> int main (int argc, char** argv) { pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>); if (pcl::io::loadPCDFile<pcl::PointXYZ> ("airplane.pcd", *cloud) == -1) //* load the file { PCL_ERROR ("Couldn't read file test_pcd.pcd \n"); return (-1); } std::cout << "Loaded " << cloud->width * cloud->height << " data points from test_pcd.pcd with the following
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