Skip to content

A lightweight and accurate point cloud clustering method

License

Notifications You must be signed in to change notification settings

Cantoluna/adaptive_clustering

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

20 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Adaptive Clustering

Build Status Codacy Badge License

A lightweight and accurate point cloud clustering method (check out the devel branch for further enrichment).

YouTube Video

How to build

$ 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}
}

About

A lightweight and accurate point cloud clustering method

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • C++ 94.5%
  • CMake 5.5%