https://github.com/yzrobot/adaptive_clustering

[ROS package] Lightweight and Accurate Point Cloud Clustering
https://github.com/yzrobot/adaptive_clustering

clustering point-cloud point-cloud-segmentation ros velodyne

Last synced: 9 days ago
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[ROS package] Lightweight and Accurate Point Cloud Clustering

• Host: GitHub
• URL: https://github.com/yzrobot/adaptive_clustering
• Owner: yzrobot
• License: bsd-3-clause
• Created: 2019-02-25T10:20:02.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2023-07-14T12:37:16.000Z (over 1 year ago)
• Last Synced: 2024-08-01T03:18:35.001Z (3 months ago)
• Topics: clustering, point-cloud, point-cloud-segmentation, ros, velodyne
• Language: C++
• Homepage:
• Size: 266 KB
• Stars: 361
• Watchers: 9
• Forks: 90
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Adaptive Clustering: A lightweight and accurate point cloud clustering method #

[![Build Status](https://travis-ci.org/yzrobot/adaptive_clustering.svg?branch=master)](https://travis-ci.org/yzrobot/adaptive_clustering)

[![Codacy Badge](https://api.codacy.com/project/badge/Grade/61a01a79a7ac41fd9deded9050ef6030)](https://www.codacy.com/app/yzrobot/adaptive_clustering?utm_source=github.com&utm_medium=referral&utm_content=yzrobot/adaptive_clustering&utm_campaign=Badge_Grade)

[![License](https://img.shields.io/badge/License-BSD%203--Clause-green.svg)](https://opensource.org/licenses/BSD-3-Clause)

[![YouTube Video](https://img.youtube.com/vi/rmPn7mWssto/0.jpg)](https://www.youtube.com/watch?v=rmPn7mWssto)

## Changelog ##

*   **\[Apr 14, 2022\]:** Two new branches, [gpu](https://github.com/yzrobot/adaptive_clustering/tree/gpu) and [agx](https://github.com/yzrobot/adaptive_clustering/tree/agx), have been created for GPU-based implementations:

    *   [gpu](https://github.com/yzrobot/adaptive_clustering/tree/gpu) is based on [PCL-GPU](https://pcl.readthedocs.io/projects/tutorials/en/master/#gpu) and has been tested with an NVIDIA TITAN Xp.

    *   [agx](https://github.com/yzrobot/adaptive_clustering/tree/agx) is based on [CUDA-PCL](https://github.com/NVIDIA-AI-IOT/cuda-pcl) and has been tested with an NVIDIA Jetson AGX Xavier.

*   **\[Feb 25, 2019\]:** A new branch, [devel](https://github.com/yzrobot/adaptive_clustering/tree/devel), faster (by downsampling) and better (by merging clusters split by nested regions and on the z-axis).

## How to build ##

```sh

cd ~/catkin_ws/src/

git clone https://github.com/yzrobot/adaptive_clustering.git

cd ~/catkin_ws

catkin_make

```

## Citation ##

If you are considering using this code, please reference the following:

```

@article{yz19auro,

   author = {Zhi Yan and Tom Duckett and Nicola Bellotto},

   title = {Online learning for 3D LiDAR-based human detection: Experimental analysis of point cloud clustering and classification methods},

   journal = {Autonomous Robots},

   year = {2019}

}

```