Open Source C++ Point Cloud Software

Intel® RealSense™ SDK 2.0 is a cross-platform library for Intel® RealSense™ depth cameras. The SDK allows depth and color streaming and provides intrinsic and extrinsic calibration information. The library also offers synthetic streams (point cloud, depth aligned to color and vise-versa), and built-in support for recording and playback of streaming sessions. Intel has EOLed the LiDAR, Facial Authentication, and Tracking product lines. These products have been discontinued and will no longer be available for new orders. Intel WILL continue to sell and support stereo products including the following: D410, D415, D430, , D401 ,D450 modules and D415, D435, D435i, D435f, D405, D455, D457 depth cameras. We will also continue the work to support and develop our LibRealSense open source SDK.

COLMAP is a general-purpose Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipeline with a graphical and command-line interface. It offers a wide range of features for the reconstruction of ordered and unordered image collections. The software is licensed under the new BSD license.

CloudCompare is a 3D point cloud (and triangular mesh) processing software. It was originally designed to perform comparison between two 3D points clouds (such as the ones obtained with a laser scanner) or between a point cloud and a triangular mesh. It relies on an octree structure that is highly optimized for this particular use-case. It was also meant to deal with huge point clouds (typically more than 10 million points, and up to 120 million with 2 GB of memory).

The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. PCL is released under the terms of the BSD license, and thus free for commercial and research use. Whether you’ve just discovered PCL or you’re a long time veteran, this page contains links to a set of resources that will help consolidate your knowledge on PCL and 3D processing. An additional Wiki resource for developers is available too. To simplify both usage and development, we split PCL into a series of modular libraries. PCL is cross-platform, and has been successfully compiled and deployed on Linux, MacOS, Windows, and Android. To simplify development, PCL is split into a series of smaller code libraries, that can be compiled separately. This modularity is important for distributing PCL on platforms with reduced computational or size constraints.

The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. PCL is released under the terms of the BSD license, and thus free for commercial and research use. We are financially supported by Open Perception, Willow Garage, NVIDIA, Google, Toyota, Trimble, Urban Robotics, Honda Research Institute, Sandia, Dinast, Optronic, Ocular Robotics, Velodyne, Fotonic, Leica Geosystems, and MKE. We would also like to thank individual donors and contributors that have been helping the project.

A suite of tools for processing and analyzing meshes and point clouds. 1) Ensuring that meshes are manifold, ie, "nice" 2) Simple smoothing/noise reduction 3) Bare-bones point cloud to mesh and robust normals for point clouds 4) Mesh simplification 5) Curvature calculation on meshes 6) Local shape descriptors on meshes

BADGr, the BoxGrasping toolbox, is a package for Box Approximation, Decomposition, and Grasping. The toolbox was developed in the Computer Vision & Active Perception Lab, at the Royal Institute of Technology, as a participant of the EU research project PACO-PLUS, and published at the project's end in Summer 2010. BADGr provides modules to approximate the shape of a point cloud (possibly from sensor data) by box primitives. These box primitives then serve as a base for the generation of box-based pre-grasp hypotheses for robot grippers.

The dynamic_robot_localization is a ROS package that offers 3 DoF and 6 DoF localization using PCL and allows dynamic map update using OctoMap. It's a modular localization pipeline, that can be configured using yaml files (detailed configuration layout available in drl_configs.yaml and examples of configurations available in guardian_config and dynamic_robot_localization_tests). Even though this package was developed for robot self-localization and mapping, it was implemented as a generic, configurable and extensible point cloud matching library, allowing its usage in related problems such as estimation of the 6 DoF pose of an object and 3D object scanning.

This project is about the implementation of algorithms studied during mathematics and computer graphic courses for my MS's last year ( Point cloud approximation, Hermitian interpolation, Bezier / B-Spline Curves, Convex Hull, Delaunay triangulation

Magic3D provides basic functions of processing 3D point cloud and mesh. http://geometryhub.net/en/magic3d

PhotoCloud is a tool to browse and a navigate for datasets composed of (a) a collection of registered images and (b) a 3D model over which images are aligned. The 3D model can be a point-cloud, triangle mesh. PhotoCloud is based on a client/server architecture and it is scalable: very large dataset (both in terms of (a) and (b) can be handled.

The Point Cloud Compiler is a tool for converting point cloud image (3D) to human-visible image (2D) by orthogonal projection.

using simple cuboids and gjk algorithm, this general purpose algorithm gives a ready made code to work with swissranger 3D camera.

Volumetric is a 3-D image processing tool. It reads point cloud data, expands it to a volumetric space with highly effective memory usage, and filter out necessary points.

XIVO is an open-source repository for visual-inertial odometry/mapping. It is a simplified version of Corvis [Jones et al.,Tsotsos et al.], designed for pedagogical purposes, and incorporates odometry (relative motion of the sensor platform), local mapping (pose relative to a reference frame of the oldest visible features), and global mapping (pose relative to a global frame, including loop-closure and global re-localization, this feature, present in Corvis, is not yet incorporated in XIVO). XIVO runs at 140FPS on stored data (here from a RealSense D435i sensor) or on live streams with a latency of around 1-7ms, depending on the hardware. It takes as input video frames from a calibrated camera and inertial measurements from an IMU and outputs a sparse point cloud with attribute features and 6 DOF pose of the camera. It performs auto-calibration of the relative pose between the camera and the IMU as well as the time-stamp alignment.

ZPR is a program that produces orthophotos. The method used is to give colors to point-cloud (photo obtained by a digital camera, cloud obtained by a laser scanner) and to project the point-cloud to a requested plane. With this method, the projection pla

Open source point cloud viewer forked from Radiohead House of Cards Project, based on the Processing Programming Language.

### mesh reconstruction from point cloud # filters the input data eliminating noise # creates a quad shell - mesh with inside and thickness ### additional info: - GUI using Clan-Lib SDK