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Technologies + Design for Social Integration Read chapter Read first chapter

2023 | OriginalPaper | Chapter

Camera and LiDAR Fusion for Point Cloud Semantic Segmentation

Authors : Ali Abdelkader, Mohamed Moustafa

Published in: Proceedings of Seventh International Congress on Information and Communication Technology

Publisher: Springer Nature Singapore

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Abstract

Perception is a fundamental component of any autonomous driving system. Semantic segmentation is the perception task of assigning semantic class labels to sensor inputs. While autonomous driving systems are currently equipped with a suite of sensors, much focus in the literature has been on semantic segmentation of camera images only. Research in the fusion of different sensor modalities for semantic segmentation has not been investigated as much. Deep learning models based on transformer architectures have proven successful in many tasks in computer vision and natural language processing. This work explores the use of deep learning transformers to fuse information from LiDAR and camera sensors to improve the segmentation of LiDAR point clouds. It also addresses the question of which fusion level in this deep learning framework provides better performance.

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Metadata
Title
Camera and LiDAR Fusion for Point Cloud Semantic Segmentation
Authors
Ali Abdelkader
Mohamed Moustafa
Copyright Year
2023
Publisher
Springer Nature Singapore
Book
Proceedings of Seventh International Congress on Information and Communication Technology

Print ISBN: 978-981-19-2393-7

Electronic ISBN: 978-981-19-2394-4

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-981-19-2394-4_45