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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

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[ROS package] Lightweight and Accurate Point Cloud Clustering

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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}
}
```