计算机视觉：点云聚类（Pointcloud Cluster）

# Adaptive Clustering: A lightweight and accurate point cloud clustering method # [](https://travis-ci.org/yzrobot/adaptive_clustering) [](https://www.codacy.com/app/yzrobot/adaptive_clustering?utm_source=github.com&utm_medium=referral&utm_content=yzrobot/adaptive_clustering&utm_campaign=Badge_Grade) [](https://opensource.org/licenses/BSD-3-Clause) [](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} } ```