LiDAR and Camera Based 3D Object Classification in Unknown Environments Using Weakly Supervised Learning

Siva Bairaju, Srinivas Yalagam, Krishna Konda

2023

Abstract

Sensor redundancy is often relied upon the method in various applications to ensure robust and secure operation. Autonomous Driving (AD) and Advanced Driver Assistance Systems (ADAS) are no exceptions. camera and LiDAR are the principle sensors that are used in both applications. LiDAR is primarily used for object localization due to its active nature. A camera on the other hand is used for object classification owing to its dense response. In this paper, we present a novel neural network and training methodology for camera-based reinforcement of LiDAR object classification. The proposed method is also useful as a domain adaptation framework in an unknown environment. A pre-trained LiDAR-based object classification network is iteratively trained based on camera classification output to achieve continual improvement while in operation. The proposed system has been tested on benchmark datasets and performs well when compared with the state of the art.

Paper Citation

in Harvard Style

Bairaju S., Yalagam S. and Konda K. (2023). LiDAR and Camera Based 3D Object Classification in Unknown Environments Using Weakly Supervised Learning. In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-626-2, pages 304-311. DOI: 10.5220/0011657700003411

in Bibtex Style

@conference{icpram23,
author={Siva Bairaju and Srinivas Yalagam and Krishna Konda},
title={LiDAR and Camera Based 3D Object Classification in Unknown Environments Using Weakly Supervised Learning},
booktitle={Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2023},
pages={304-311},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011657700003411},
isbn={978-989-758-626-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - LiDAR and Camera Based 3D Object Classification in Unknown Environments Using Weakly Supervised Learning
SN - 978-989-758-626-2
AU - Bairaju S.
AU - Yalagam S.
AU - Konda K.
PY - 2023
SP - 304
EP - 311
DO - 10.5220/0011657700003411