Towards Depth Perception from Noisy Camera based Sensors for Autonomous Driving

Mena Nagiub, Thorsten Beuth

2022

Abstract

Autonomous driving systems use depth sensors to create 3D point clouds of the scene. They use 3D point clouds as a building block for other driving algorithms. Depth completion and prediction methods are used to improve depth information and inaccuracy. Accuracy is a cornerstone of automotive safety. This paper studies different depth completion and prediction methods providing an overview of the methods’ accuracies and use cases. The study is limited to low-speed driving scenarios based on standard cameras and Laser sensors.

Paper Citation

in Harvard Style

Nagiub M. and Beuth T. (2022). Towards Depth Perception from Noisy Camera based Sensors for Autonomous Driving. In Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-573-9, pages 198-207. DOI: 10.5220/0010989800003191

in Bibtex Style

@conference{vehits22,
author={Mena Nagiub and Thorsten Beuth},
title={Towards Depth Perception from Noisy Camera based Sensors for Autonomous Driving},
booktitle={Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2022},
pages={198-207},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010989800003191},
isbn={978-989-758-573-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Towards Depth Perception from Noisy Camera based Sensors for Autonomous Driving
SN - 978-989-758-573-9
AU - Nagiub M.
AU - Beuth T.
PY - 2022
SP - 198
EP - 207
DO - 10.5220/0010989800003191