Online learning for human classification in 3D LiDAR-based tracking
This is a ROS-based online learning framework for human classification in 3D LiDAR scans, taking advantage of robust multi-target tracking to avoid the need for data annotation by a human expert. Please watch the videos below for more details.
For a standalone implementation of the clustering method, please refer to: https://github.com/yzrobot/adaptive_clustering
How to build
$ cd ~/catkin_ws/src/
$ git clone https://github.com/yzrobot/online_learning.git
$ cd ~/catkin_ws
$ catkin_make
Citation
If you are considering using this code, please reference the following:
@inproceedings{yz17iros,
author = {Zhi Yan and Tom Duckett and Nicola Bellotto},
title = {Online learning for human classification in {3D LiDAR-based} tracking},
booktitle = {In Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
pages = {864--871},
address = {Vancouver, Canada},
month = {September},
year = {2017}
}