@inproceedings{0d500483d56d41b781ce961fe9431586,
title = "Towards Depth Perception from Noisy Camera based Sensors for Autonomous Driving",
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{\textquoteright} accuracies and use cases. The study is limited to low-speed driving scenarios based on standard cameras and Laser sensors.",
keywords = "Camera-based Sensors, Dense Depth Completion, LIDAR, Monocular Depth Prediction, Noise",
author = "Mena Nagiub and Thorsten Beuth",
note = "Publisher Copyright: Copyright {\textcopyright} 2022 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.; 8th International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2022 ; Conference date: 27-04-2022 Through 29-04-2022",
year = "2022",
doi = "10.5220/0010989800003191",
language = "English",
series = "International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS - Proceedings",
publisher = "Science and Technology Publications, Lda",
pages = "198--207",
editor = "Jeroen Ploeg and Jeroen Ploeg and Markus Helfert and Karsten Berns and Oleg Gusikhin",
booktitle = "Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2022",
}