Segmentation of 3D Point Cloud

Introduction

Code for implementation of the paper titled : Fast Segmentation of 3D Point Clouds: A Paradigm on LiDAR Data for Autonomous Vehicle Applications.

Overview of the Repository

In this repo, you'll find :

• pointclouds: point clouds dataset.
• paper.pdf: the paper of Fast Segmentation of 3D Point Clouds.
• gpf.py: ground plane fitting (GPF) algorithm from 3D lidar scan shot in the street.
• pypcd: folder for mapping between PointField types and numpy types, extracting PointCloud object from a dataframe, etc.

Getting Started

1. Clone repo: git clone https://github.com/HusseinLezzaik/Segmentation-of-3D-Point-Cloud.git
2. Install dependencies:

   conda create -n segmentation-point-clouds python=3.7
   conda activate segmentation-point-clouds
   pip install -r requirements.txt
   

Contact

• Hussein Lezzaik : hussein dot lezzaik at gmail dot com