Displaying 1 to 9 from 9 results

TEASER-plusplus - A fast and robust point cloud registration library

  •    C++

TEASER++ is a fast and certifiably-robust point cloud registration library written in C++, with Python and MATLAB bindings. Left: correspondences generated by 3DSmoothNet (green and red lines represent the inlier and outlier correspondences according to the ground truth respectively). Right: alignment estimated by TEASER++ (green dots represent inliers found by TEASER++).

lidar_camera_calibration - ROS package to find a rigid-body transformation between a LiDAR and a camera for "LiDAR-Camera Calibration using 3D-3D Point correspondences"

  •    C++

The package is used to calibrate a LiDAR (config to support Hesai and Velodyne hardware) with a camera (works for both monocular and stereo). The package finds a rotation and translation that transform all the points in the LiDAR frame to the (monocular) camera frame. Please see Usage for a video tutorial. The lidar_camera_calibration/pointcloud_fusion provides a script to fuse point clouds obtained from two stereo cameras. Both of which were extrinsically calibrated using a LiDAR and lidar_camera_calibration. We show the accuracy of the proposed pipeline by fusing point clouds, with near perfection, from multiple cameras kept in various positions. See Fusion using lidar_camera_calibration for results of the point cloud fusion (videos).

nanoflann - nanoflann: a C++11 header-only library for Nearest Neighbor (NN) search with KD-trees

  •    C++

nanoflann is a C++11 header-only library for building KD-Trees of datasets with different topologies: R2, R3 (point clouds), SO(2) and SO(3) (2D and 3D rotation groups). No support for approximate NN is provided. nanoflann does not require compiling or installing. You just need to #include <nanoflann.hpp> in your code. This library is a fork of the flann library by Marius Muja and David G. Lowe, and born as a child project of MRPT. Following the original license terms, nanoflann is distributed under the BSD license. Please, for bugs use the issues button or fork and open a pull request.

point_labeler - My awesome point cloud labeling tool

  •    C++

Tool for labeling of a single point clouds or a stream of point clouds. Given the poses of a KITTI point cloud dataset, we load tiles of overlapping point clouds. Thus, multiple point clouds are labeled at once in a certain area.




pyntcloud - pyntcloud is a Python library for working with 3D point clouds.

  •    Python

pyntcloud is a Python 3 library for working with 3D point clouds leveraging the power of the Python scientific stack. You can access most of pyntcloud's functionality from its core class: PyntCloud.

PDollar-Unity - PDollar algorithm Unity friendly

  •    CSharp

Original article. Unity Web demo. This is an adaptation of the original C# code for Unity.

mp2p_icp - Multi primitive-to-primitive (MP2P) ICP algorithms in C++

  •    C++

A repertory of multi primitive-to-primitive (MP2P) ICP algorithms in C++.


LiDARTag - This is a package for LiDARTag, described in paper: LiDARTag: A Real-Time Fiducial Tag System for Point Clouds

  •    Jupyter

This is a package for LiDARTag, described in paper: LiDARTag: A Real-Time Fiducial Tag System for Point Clouds (PDF)(arXiv). This work is accepted by IEEE Robotics and Automation Letters and published at (here). Image-based fiducial markers are useful in problems such as object tracking in cluttered or textureless environments, camera (and multi-sensor) calibration tasks, and vision-based simultaneous localization and mapping (SLAM). However, the state-of-the-art fiducial marker detection algorithms rely on the consistency of the ambient lighting. To the best of our knowledge, there are no existing fiducial markers for point clouds.






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