https://github.com/berensrwu/pointcloud_distortion

Some functions to distort a point cloud.
https://github.com/berensrwu/pointcloud_distortion

Last synced: about 1 month ago
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Some functions to distort a point cloud.

• Host: GitHub
• URL: https://github.com/berensrwu/pointcloud_distortion
• Owner: BerensRWU
• Created: 2024-07-29T12:07:19.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-08-21T14:32:53.000Z (4 months ago)
• Last Synced: 2024-08-21T16:18:39.530Z (4 months ago)
• Language: Jupyter Notebook
• Size: 6.84 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# PointCloud_Distortion

This repository contains a Python implementation for simulating various disturbances on point cloud data, typically generated by LiDAR or RADAR sensors. These disturbances are intended to model real-world scenarios where sensor data might be affected by various environmental or technical factors, helping to evaluate the robustness of algorithms that process point cloud data.

Features

* Add Points: Randomly adds new points to the existing point cloud within a specified Region of Interest (ROI).

* Lose Points: Randomly removes a portion of the points from the point cloud, simulating data loss

* *Shifting: Applies random shifts to the points in the point cloud, simulating calibration errors or mechanical vibrations

* Cluster: Adds groups of points to the point cloud, simulating local disturbances like dust, smoke, or interference

* Information Noise: Adds noise to the additional information (e.g., intensity, magnitude) associated with each point, simulating measurement errors.

# Further Repositories

* Fog simulation: https://github.com/MartinHahner/LiDAR_fog_sim

* Snow simulation: https://github.com/SysCV/LiDAR_snow_sim