The following links describe a set of basic PCL tutorials. Please note that their 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 tutorials below is automatically generated from reST files located in our git repository.
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 your contributions on any tutorial.
walkthrough
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.
basic_structures
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.
using_pcl_pcl_config
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.
compiling_pcl_posix
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.
building_pcl
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.
compiling_pcl_dependencies_windows
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.
compiling_pcl_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.
compiling_pcl_macosx
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.
installing_homebrew
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.
using_pcl_with_eclipse
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.
generate_local_doc
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.
matrix_transform
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.
adding_custom_ptype
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.
writing_new_classes
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.
how_3d_features_work
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.
normal_estimation
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.
normal_estimation_using_integral_images
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.
pfh_estimation
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.
fpfh_estimation
Title: Fast Point Feature Histograms (FPFH) descriptors
Author: Radu B. Rusu
Compatibility: > PCL 1.3
This tutorial introduces the FPFH (Fast Point Feature Histograms) 3D descriptor and discusses their implementation details from PCL's perspective.
vfh_estimation
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.
narf_feature_extraction
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.
moment_of_inertia
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.
rops_feature
Title: RoPs (Rotational Projection Statistics) feature
Author: Sergey Ushakov
Compatibility: > PCL 1.7
In this tutorial we will learn how to compute RoPS feature.
gasd_estimation
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.
passthrough
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.
voxelgrid
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.
statistical_outlier_removal
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.
project_inliers
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).
extract_indices
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.
remove_outliers
Title: Removing outliers using a Conditional or RadiusOutlier removal
Author: Gabe O'Leary
Compatibility: > PCL 1.0
In this tutorial, we will learn how to remove outliers from noisy data, using ConditionalRemoval, RadiusOutlierRemoval.
pcd_file_format
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.
reading_pcd
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.
writing_pcd
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.
concatenate_clouds
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.
openni_grabber
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.
hdl_grabber
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.
dinast_grabber
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.
ensenso_cameras
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.
david_sdk
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.
depth_sense_grabber
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.
narf_keypoint_extraction
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.
kdtree_search
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
octree_compression
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.
octree_search
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.
octree_change_detection
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.
range_image_creation
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.
range_image_border_extraction
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.
correspondence_grouping
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.
implicit_shape_model
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.
global_hypothesis_verification
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.
registration_api
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.
iterative_closest_point
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.
pairwise_incremental_registration
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.
interactive_icp
Title: Interactive ICP
Author: Victor Lamoine
Compatibility: > PCL 1.5
This tutorial will teach you how to build an interactive ICP program
normal_distributions_transform
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.
in_hand_scanner
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.
alignment_prerejective
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.
random_sample_consensus
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.
planar_segmentation
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.
cylinder_segmentation
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.
cluster_extraction
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::EuclideanClusterExtractionclass.
region_growing_segmentation
Title: Region Growing Segmentation
Author: Sergey Ushakov
Compatibility: >= PCL 1.7
In this tutorial we will learn how to use region growing segmentation algorithm.
region_growing_rgb_segmentation
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.
min_cut_segmentation
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.
conditional_euclidean_clustering
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.
don_segmentation
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.
supervoxel_clustering
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.
progressive_morphological_filtering
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.
model_outlier_removal
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
moving_least_squares
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.
hull_2d
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.
greedy_triangulation
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.
bspline_fitting
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.
cloud_viewer
Title: Visualizing Point Clouds
Author: Ethan Rublee
Compatibility: > PCL 1.0
This tutorial demonstrates how to use the pcl visualization tools.
range_image_visualization
Title: Visualizing Range Images
Author: Bastian Steder
Compatibility: > PCL 1.3
This tutorial demonstrates how to use the pcl visualization tools for range images.
pcl_visualizer
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.
pcl_plotter
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.
visualization
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.
qt_visualizer
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.
qt_colorize_cloud
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.
template_alignment
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.
vfh_recognition
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.
mobile_streaming
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.
ground_based_rgbd_people_detection
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.
gpu_install
Title: GPU Installation
Author: Koen Buys
Compatibility: PCL git master
This tutorial explains how to configure PCL to use with a Nvidia GPU
using_kinfu_large_scale
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.
gpu_people
Title: People Detection
Author: Koen Buys
Compatibility: PCL git master
This tutorial presents a method for people and pose detection.