Non Euclidean Room Mac OS

The following links describe a set of basic PCL tutorials. Please note thattheir source codes may already be provided as part of the PCL regular releases,so check there before you start copy & pasting the code. The list of tutorialsbelow is automatically generated from reST files located in our git repository.

Interactive geometry software (IGS) or dynamic geometry environments (DGEs) are computer programs which allow one to create and then manipulate geometric constructions, primarily in plane geometry.In most IGS, one starts construction by putting a few points and using them to define new objects such as lines, circles or other points. After some construction is done, one can move the points one. When you think they've created everything there is to create in the world of video games! This game is so different and SO WEIRD! When I finished record.

Note

Before you start reading, please make sure that you go through the higher-level overview documentation at http://www.pointclouds.org/documentation/, under Getting Started. Thank you.

As always, we would be happy to hear your comments and receive yourcontributions on any tutorial.

  • Title: PCL Functionality Walkthrough

    Author: Razvan G. Mihalyi

    Compatibility: > PCL 1.6

    Takes the reader through all of the PCL modules and offers basic explanations on their functionalities.

  • Title: Getting Started / Basic Structures

    Author: Radu B. Rusu

    Compatibility: > PCL 1.0

    Presents the basic data structures in PCL and discusses their usage with a simple code example.

  • Title: Using PCL in your own project

    Author: Nizar Sallem

    Compatibility: > PCL 1.0

    In this tutorial, we will learn how to link your own project to PCL using cmake.

  • Title: Compiling PCL from source on POSIX compliant systems

    Author: Victor Lamoine

    Compatibility: > PCL 1.0

    In this tutorial, we will explain how to compile PCL from sources on POSIX/Unix systems.

  • Title: Explaining PCL’s cmake options

    Author: Nizar Sallem

    Compatibility: > PCL 1.0

    In this tutorial, we will explain the basic PCL cmake options, and ways to tweak them to fit your project.

  • Title: Compiling PCL’s dependencies from source on Windows

    Authors: Alessio Placitelli and Mourad Boufarguine

    Compatibility: > PCL 1.0

    In this tutorial, we will explain how to compile PCL’s 3rd party dependencies from source on Microsoft Windows.

  • Title: Compiling PCL on Windows

    Author: Mourad Boufarguine

    Compatibility: > PCL 1.0

    In this tutorial, we will explain how to compile PCL on Microsoft Windows.

  • Title: Compiling PCL and its dependencies from MacPorts and source on Mac OS X

    Author: Justin Rosen

    Compatibility: > PCL 1.0

    This tutorial explains how to build the Point Cloud Library from MacPorts and source on Mac OS X platforms.

  • Title: Installing on Mac OS X using Homebrew

    Author: Geoffrey Biggs

    Compatibility: > PCL 1.2

    This tutorial explains how to install the Point Cloud Library on Mac OS X using Homebrew. Both direct installation and compiling PCL from source are explained.

  • Title: Using Eclipse as your PCL editor

    Author: Koen Buys

    Compatibility: PCL git master

    This tutorial shows you how to get your PCL as a project in Eclipse.

  • Title: Generate a local documentation for PCL

    Author: Victor Lamoine

    Compatibility: PCL > 1.0

    This tutorial shows you how to generate and use a local documentation for PCL.

  • Title: Using matrixes to transform a point cloud

    Author: Victor Lamoine

    Compatibility: > PCL 1.5

    This tutorial shows you how to transform a point cloud using a matrix.

Non euclidean structure
  • Title: Adding your own custom PointT point type

    Author: Radu B. Rusu

    Compatibility: > PCL 0.9, < PCL 2.0

    This document explains what templated point types are in PCL, why do they exist, and how to create and use your own PointT point type.

  • Title: Writing a new PCL class

    Author: Radu B. Rusu, Luca Penasa

    Compatibility: > PCL 0.9, < PCL 2.0

    This short guide is to serve as both a HowTo and a FAQ for writing new PCL classes, either from scratch, or by adapting old code.

  • Title: How 3D features work

    Author: Radu B. Rusu

    Compatibility: > PCL 1.0

    This document presents a basic introduction to the 3D feature estimation methodologies in PCL.

  • Title: Estimating Surface Normals in a PointCloud

    Author: Radu B. Rusu

    Compatibility: > PCL 1.0

    This tutorial discusses the theoretical and implementation details of the surface normal estimation module in PCL.

  • Title: Normal Estimation Using Integral Images

    Author: Stefan Holzer

    Compatibility: > PCL 1.0

    In this tutorial we will learn how to compute normals for an organized point cloud using integral images.

  • Title: Point Feature Histograms (PFH) descriptors

    Author: Radu B. Rusu

    Compatibility: > PCL 1.0

    This tutorial introduces a family of 3D feature descriptors called PFH (Point Feature Histograms) and discusses their implementation details from PCL’s perspective.

  • Title: Fast Point Feature Histograms (FPFH) descriptors

    Author: Radu B. RusuBug off! mac os.

    Compatibility: > PCL 1.3

    This tutorial introduces the FPFH (Fast Point Feature Histograms) 3D descriptor and discusses their implementation details from PCL’s perspective.

  • Title: Estimating VFH signatures for a set of points

    Author: Radu B. Rusu

    Compatibility: > PCL 0.8

    This document describes the Viewpoint Feature Histogram (VFH) descriptor, a novel representation for point clusters for the problem of Cluster (e.g., Object) Recognition and 6DOF Pose Estimation.

  • Title: How to extract NARF features from a range image

    Author: Bastian Steder

    Compatibility: > 1.3

    In this tutorial, we will learn how to extract NARF features from a range image.

  • Title: Moment of inertia and eccentricity based descriptors

    Author: Sergey Ushakov

    Compatibility: > PCL 1.7

    In this tutorial we will learn how to compute moment of inertia and eccentricity of the cloud. In addition to this we will learn how to extract AABB and OBB.

  • Title: RoPs (Rotational Projection Statistics) feature

    Author: Sergey Ushakov

    Compatibility: > PCL 1.7

    In this tutorial we will learn how to compute RoPS feature.

  • Title: Globally Aligned Spatial Distribution (GASD) descriptors

    Author: Joao Paulo Lima

    Compatibility: >= PCL 1.9

    This document describes the Globally Aligned Spatial Distribution (GASD) global descriptor to be used for efficient object recognition and pose estimation.

  • Title: Filtering a PointCloud using a PassThrough filter

    Author: Radu B. Rusu

    Compatibility: > PCL 1.0

    In this tutorial, we will learn how to remove points whose values fall inside/outside a user given interval along a specified dimension.

  • Title: Downsampling a PointCloud using a VoxelGrid filter

    Author: Radu B. Rusu

    Compatibility: > PCL 1.0

    In this tutorial, we will learn how to downsample (i.e., reduce the number of points) a Point Cloud.

  • Title: Removing sparse outliers using StatisticalOutlierRemoval

    Author: Radu B. Rusu

    Compatibility: > PCL 1.0

    In this tutorial, we will learn how to remove sparse outliers from noisy data, using StatisticalRemoval.

  • Title: Projecting points using a parametric model

    Author: Radu B. Rusu

    Compatibility: > PCL 1.0

    In this tutorial, we will learn how to project points to a parametric model (i.e., plane).

  • Title: Extracting indices from a PointCloud

    Author: Radu B. Rusu

    Compatibility: > PCL 1.0

    In this tutorial, we will learn how to extract a set of indices given by a segmentation algorithm.

  • Title: Removing outliers using a Conditional or RadiusOutlier removal

    Author: Gabe O’Leary

    New aristocrat slot machines. Compatibility: > PCL 1.0

    In this tutorial, we will learn how to remove outliers from noisy data, using ConditionalRemoval, RadiusOutlierRemoval.

  • Title: The PCD (Point Cloud Data) file format

    Author: Radu B. Rusu

    Compatibility: > PCL 0.9

    This document describes the PCD file format, and the way it is used inside PCL.

  • Title: Reading Point Cloud data from PCD files

    Author: Radu B. Rusu

    Compatibility: > PCL 1.0

    In this tutorial, we will learn how to read a Point Cloud from a PCD file.

  • Title: Writing Point Cloud data to PCD files

    Author: Radu B. Rusu

    Compatibility: > PCL 1.0

    In this tutorial, we will learn how to write a Point Cloud to a PCD file.

  • Title: Concatenate the fields or points of two Point Clouds

    Author: Gabe O’Leary / Radu B. Rusu

    Compatibility: > PCL 1.0

    In this tutorial, we will learn how to concatenate both the fields and the point data of two Point Clouds. When concatenating fields, one PointClouds contains only XYZ data, and the other contains Surface Normal information.

  • Title: Grabbing Point Clouds from an OpenNI camera

    Author: Nico Blodow

    Compatibility: > PCL 1.0

    In this tutorial, we will learn how to acquire point cloud data from an OpenNI camera.

  • Title: Grabbing Point Clouds from a Velodyne High Definition LiDAR (HDL)

    Author: Keven Ring

    Compatibility: >= PCL 1.7

    In this tutorial, we will learn how to acquire point cloud data from a Velodyne HDL.

  • Title: Grabbing Point Clouds from Dinast Cameras

    Author: Marco A. Gutierrez

    Compatibility: >= PCL 1.7

    In this tutorial, we will learn how to acquire point cloud data from a Dinast camera.

  • Title: Grabbing point clouds from Ensenso cameras

    Author: Victor Lamoine

    Compatibility: >= PCL 1.8.0

    In this tutorial, we will learn how to acquire point cloud data from an IDS-Imaging Ensenso camera.

  • Title: Grabbing point clouds / meshes from davidSDK scanners

    Author: Victor Lamoine

    Compatibility: >= PCL 1.8.0

    In this tutorial, we will learn how to acquire point cloud or mesh data from a davidSDK scanner.

  • Title: Grabbing point clouds from DepthSense cameras

    Author: Sergey Alexandrov

    Compatibility: >= PCL 1.8.0

    In this tutorial we will learn how to setup and use DepthSense cameras within PCL on both Linux and Windows platforms.

  • Title: How to extract NARF keypoints from a range image

    Author: Bastian Steder

    Compatibility: > 1.3

    In this tutorial, we will learn how to extract NARF keypoints from a range image.

  • Title: KdTree Search

    Author: Gabe O’Leary

    Compatibility: > PCL 1.0

    In this tutorial, we will learn how to search using the nearest neighbor method for k-d trees

  • Title: Point cloud compression

    Author: Julius Kammerl

    Compatibility: > PCL 1.0

    In this tutorial, we will learn how to compress a single point cloud and streams of point clouds.

  • Title: Octrees for spatial partitioning and neighbor search

    Author: Julius Kammerl

    Compatibility: > PCL 1.0

    In this tutorial, we will learn how to use octrees for spatial partitioning and nearest neighbor search.

  • Title: Spatial change detection on unorganized point cloud data

    Author: Julius Kammerl

    Compatibility: > PCL 1.0

    In this tutorial, we will learn how to use octrees for detecting spatial changes within point clouds.

Non Euclidean Room Mac Os Download

  • Title: Creating Range Images from Point Clouds

    Author: Bastian Steder

    Compatibility: > PCL 1.0

    This tutorial demonstrates how to create a range image from a point cloud and a given sensor position.

  • Title: Extracting borders from Range Images

    Author: Bastian Steder

    Compatibility: > PCL 1.3

    This tutorial demonstrates how to extract borders (traversals from foreground to background) from a range image.

  • Title: The PCL Recognition API

    Author: Tommaso Cavallari, Federico Tombari

    Compatibility: > PCL 1.6

    This tutorial aims at explaining how to perform 3D Object Recognition based on the pcl_recognition module.

  • Title: Implicit Shape Model

    Author: Sergey Ushakov

    Compatibility: > PCL 1.7

    In this tutorial we will learn how the Implicit Shape Model algorithm works and how to use it for finding objects centers.

  • Title: Hypothesis Verification for 3D Object Recognition

    Author: Daniele De Gregorio, Federico Tombari

    Compatibility: > PCL 1.7

    This tutorial aims at explaining how to do 3D object recognition in clutter by verifying model hypotheses in cluttered and heavily occluded 3D scenes.

  • Title: The PCL Registration API

    Author: Dirk Holz, Radu B. Rusu, Jochen Sprickerhof

    Compatibility: > PCL 1.5

    In this document, we describe the point cloud registration API and its modules: the estimation and rejection of point correspondences, and the estimation of rigid transformations.

  • Title: How to use iterative closest point algorithm

    Author: Gabe O’Leary

    Compatibility: > PCL 1.0

    This tutorial gives an example of how to use the iterative closest point algorithm to see if one PointCloud is just a rigid transformation of another PointCloud.

  • Title: How to incrementally register pairs of clouds

    Author: Raphael Favier

    Compatibility: > PCL 1.4

    This document demonstrates using the Iterative Closest Point algorithm in order to incrementally register a series of point clouds two by two.

  • Title: Interactive ICP

    Author: Victor Lamoine

    Compatibility: > PCL 1.5

    This tutorial will teach you how to build an interactive ICP program

  • Title: How to use the Normal Distributions Transform algorithm

    Author: Brian Okorn

    Compatibility: > PCL 1.6

    This document demonstrates using the Normal Distributions Transform algorithm to register two large point clouds.

  • Title: How to use the In-hand scanner for small objects

    Author: Martin Saelzle

    Compatibility: >= PCL 1.7

    This document shows how to use the In-hand scanner applications to obtain colored models of small objects with RGB-D cameras.

  • Title: Robust pose estimation of rigid objects

    Author: Anders Glent Buch

    Compatibility: >= PCL 1.7

    In this tutorial, we show how to find the alignment pose of a rigid object in a scene with clutter and occlusions.

  • Title: How to use Random Sample Consensus model

    Author: Gabe O’Leary

    Compatibility: > PCL 1.0

    In this tutorial we learn how to use a RandomSampleConsensus with a plane model to obtain the cloud fitting to this model.

Non Euclidean Minecraft

  • Title: Plane model segmentation

    Author: Radu B. Rusu

    Compatibility: > PCL 1.3

    In this tutorial, we will learn how to segment arbitrary plane models from a given point cloud dataset.

  • Title: Cylinder model segmentation

    Author: Radu B. Rusu

    Compatibility: > PCL 1.3

    In this tutorial, we will learn how to segment arbitrary cylindrical models from a given point cloud dataset.

  • Title: Euclidean Cluster Extraction

    Author: Serkan Tuerker

    Compatibility: > PCL 1.3

    In this tutorial we will learn how to extract Euclidean clusters with the pcl::EuclideanClusterExtraction class.

  • Title: Region Growing Segmentation

    Author: Sergey Ushakov

    Compatibility: >= PCL 1.7

    In this tutorial we will learn how to use region growing segmentation algorithm.

  • Title: Color-based Region Growing Segmentation

    Author: Sergey Ushakov

    Compatibility: >= PCL 1.7

    In this tutorial we will learn how to use color-based region growing segmentation algorithm.

  • Title: Min-Cut Based Segmentation

    Author: Sergey Ushakov

    Compatibility: >= PCL 1.7

    In this tutorial we will learn how to use min-cut based segmentation algorithm.

  • Title: Conditional Euclidean Clustering

    Author: Frits Florentinus

    Compatibility: >= PCL 1.7

    This tutorial describes how to use the Conditional Euclidean Clustering class in PCL:A segmentation algorithm that clusters points based on Euclidean distance and a user-customizable condition that needs to hold.

  • Title: Difference of Normals Based Segmentation

    Author: Yani Ioannou

    Compatibility: >= PCL 1.7

    In this tutorial we will learn how to use the difference of normals feature for segmentation.

  • Title: Supervoxel Clustering

    Author: Jeremie Papon

    Compatibility: >= PCL 1.8

    In this tutorial, we show to break a pointcloud into the mid-level supervoxel representation.

  • Title: Progressive Morphological Filtering

    Author: Brad Chambers

    Compatibility: >= PCL 1.8

    In this tutorial, we show how to segment a point cloud into ground and non-ground returns.

  • Title: Model outlier removal

    Author: Timo Häckel

    Compatibility: >= PCL 1.7.2

    This tutorial describes how to extract points from a point cloud using SAC models

  • Title: Smoothing and normal estimation based on polynomial reconstruction

    Author: Zoltan-Csaba Marton, Alexandru E. Ichim

    Compatibility: > PCL 1.6

    In this tutorial, we will learn how to construct and run a Moving Least Squares (MLS) algorithm to obtain smoothed XYZ coordinates and normals.

  • Title: Construct a concave or convex hull polygon for a plane model

    Author: Gabe O’Leary, Radu B. Rusu

    Compatibility: > PCL 1.0

    In this tutorial we will learn how to calculate a simple 2D concave or convex hull polygon for a set of points supported by a plane.

  • Title: Fast triangulation of unordered point clouds

    Author: Zoltan-Csaba Marton

    Compatibility: > PCL 1.0

    In this tutorial we will learn how to run a greedy triangulation algorithm on a PointCloud with normals to obtain a triangle mesh based on projections of the local neighborhood.

  • Title: Fitting trimmed B-splines to unordered point clouds

    Author: Thomas Mörwald

    Compatibility: > PCL 1.7

    In this tutorial we will learn how to reconstruct a smooth surface from an unordered point-cloud by fitting trimmed B-splines.

  • Title: Visualizing Point Clouds

    Author: Ethan Rublee

    Compatibility: > PCL 1.0

    This tutorial demonstrates how to use the pcl visualization tools.

  • Title: Visualizing Range Images

    Author: Bastian Steder

    Compatibility: > PCL 1.3

    This tutorial demonstrates how to use the pcl visualization tools for range images.

  • Title: PCLVisualizer

    Author: Geoffrey Biggs

    Compatibility: > PCL 1.3

    This tutorial demonstrates how to use the PCLVisualizer class for powerful visualisation of point clouds and related data.

  • Title: PCLPlotter

    Author: Kripasindhu Sarkar

    Compatibility: > PCL 1.7

    This tutorial demonstrates how to use the PCLPlotter class for powerful visualisation of plots, charts and histograms of raw data and explicit functions.

  • Title: PCL Visualization overview

    Author: Radu B. Rusu

    Compatibility: >= PCL 1.0

    This tutorial will give an overview on the usage of the PCL visualization tools.

  • Title: Create a PCL visualizer in Qt with cmake

    Author: Victor Lamoine

    Compatibility: > PCL 1.5

    This tutorial shows you how to create a PCL visualizer within a Qt application.

  • Title: Create a PCL visualizer in Qt to colorize clouds

    Author: Victor Lamoine

    Compatibility: > PCL 1.5

    This tutorial shows you how to color point clouds within a Qt application.

Non Euclidean Room Mac Os 11

  • Title: Aligning object templates to a point cloud

    Author: Michael Dixon

    Compatibility: > PCL 1.3

    This tutorial gives an example of how some of the tools covered in the previous tutorials can be combined to solve a higher level problem — aligning a previously captured model of an object to some newly captured data.

  • Title: Cluster Recognition and 6DOF Pose Estimation using VFH descriptors

    Author: Radu B. Rusu

    Compatibility: > PCL 0.8

    In this tutorial we show how the Viewpoint Feature Histogram (VFH) descriptor can be used to recognize similar clusters in terms of their geometry.

  • Title: Point Cloud Streaming to Mobile Devices with Real-time Visualization

    Author: Pat Marion

    Compatibility: > PCL 1.3

    This tutorial describes how to send point cloud data over the network from a desktop server to a client running on a mobile device.

  • Title: Detecting people on a ground plane with RGB-D data

    Author: Matteo Munaro

    Compatibility: >= PCL 1.7

    This tutorial presents a method for detecting people on a ground plane with RGB-D data.

Non Euclidean Room Mac Os Pro

  • Title: GPU Installation

    Author: Koen Buys

    Compatibility: PCL git master

    This tutorial explains how to configure PCL to use with a Nvidia GPU

  • Title: Using Kinfu Large Scale to generate a textured mesh

    Author: Francisco Heredia and Raphael Favier

    Compatibility: PCL git master

    This tutorial demonstrates how to use KinFu Large Scale to produce a mesh from a room, and apply texture information in post-processing for a more appealing visual result.

  • Title: People Detection

    Author: Koen Buys

    Compatibility: PCL git master

    This tutorial presents a method for people and pose detection.