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Authors: Anderson Souza 1 ; Leonardo Souto 2 ; Fabio Fonseca de Oliveira 2 ; Biswa Nath Datta 3 and Luiz M. G. Gonçalves 2

Affiliations: 1 University of the State of Rio Grande do Norte, Brazil ; 2 Federal University of the Rio Grande do Norte, Brazil ; 3 Northern Illinois University, United States

ISBN: 978-989-758-264-6

Keyword(s): Visual Odometry, Polynomial Eigenvalue Problem, Motion Estimation.

Related Ontology Subjects/Areas/Topics: Autonomous Agents ; Image Processing ; Informatics in Control, Automation and Robotics ; Robotics and Automation ; Vision, Recognition and Reconstruction

Abstract: Visual Odometry (VO) is the process of calculating the motion of an agent (such as, robot and vehicle), using images captured by a single or multiple cameras embedded to it. VO is an important process to supplement autonomous navigation systems, since VO can provide accurate trajectory estimates. However, algorithms of VO work with several steps of hard numerical computation which generate numerical errors and demand considerable processing time. In this paper, we propose the use of a mathematical framework for monocular VO process based on Polynomial Eigenvalue Problem (PEP) modeling in order to achieve both more accurate motion estimation and to decrease the processing time of the VO process. Some previous experiments are shown in order to validate the proposed computation accuracy.

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Paper citation in several formats:
Souza, A.; Souza, A.; Souto, L.; de Oliveira, F.; Datta, B. and Gonçalves, L. (2017). Using Polynomial Eigenvalue Problem Modeling to Improve Visual Odometry for Autonomous Vehicles.In Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-264-6, pages 502-507. DOI: 10.5220/0006478005020507

@conference{icinco17,
author={Anderson Souza. and Anderson Souza. and Leonardo Souto. and Fabio Fonseca de Oliveira. and Biswa Nath Datta. and Luiz M. G. Gon\c{C}alves.},
title={Using Polynomial Eigenvalue Problem Modeling to Improve Visual Odometry for Autonomous Vehicles},
booktitle={Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2017},
pages={502-507},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006478005020507},
isbn={978-989-758-264-6},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - Using Polynomial Eigenvalue Problem Modeling to Improve Visual Odometry for Autonomous Vehicles
SN - 978-989-758-264-6
AU - Souza, A.
AU - Souza, A.
AU - Souto, L.
AU - de Oliveira, F.
AU - Datta, B.
AU - Gonçalves, L.
PY - 2017
SP - 502
EP - 507
DO - 10.5220/0006478005020507

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