Showing 4 open source projects for "3d point cloud processing"

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  • 1
    Point Cloud Library

    Point Cloud Library

    A standalone, large scale, open project for 2D/3D image processing

    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.
    Downloads: 77 This Week
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  • 2
    Easy3D

    Easy3D

    Efficient library for processing 3D data

    Easy3D is a lightweight, easy-to-use, and efficient library for processing and rendering 3D data, implemented in C++ with Python bindings. It is designed for tasks such as 3D modeling, geometry processing, and rendering, emphasizing simplicity and efficiency. Easy3D serves as a valuable tool for research, education, and the development of sophisticated 3D applications, providing a solid foundation for handling 3D data.
    Downloads: 217 This Week
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  • 3
    Open3D

    Open3D

    A modern library for 3D data processing

    Open3D is an open-source library that supports rapid development of software that deals with 3D data. The Open3D frontend exposes a set of carefully selected data structures and algorithms in both C++ and Python. The backend is highly optimized and is set up for parallelization. Open3D was developed from a clean slate with a small and carefully considered set of dependencies. It can be set up on different platforms and compiled from source with minimal effort. The code is clean, consistently...
    Downloads: 20 This Week
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  • 4
    FasterLIO

    FasterLIO

    Faster-LIO: Lightweight Tightly Coupled Lidar-inertial Odometry

    Faster-LIO is a lightweight, tightly coupled LiDAR-inertial odometry system for pose tracking and point-cloud mapping. It builds on FastLIO2 while replacing key spatial operations with parallel sparse incremental voxels. The design targets high update rates for both solid-state and spinning LiDAR sensors. It fuses LiDAR measurements with inertial data through an iterative Kalman-filter-based estimation pipeline. The software supports online ROS operation as well as offline processing of recorded bag files. ...
    Downloads: 0 This Week
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