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Efficient image mosaicing for multi-robot visual underwater mapping

Robotic platforms have advanced greatly in terms of their remote sensing capabilities, including obtaining optical information using cameras. Alongside these advances, visual mapping has become a very active research area, which facilitates the mapping of areas inaccessible to humans. This requires the efficient processing of data to increase the final mosaic quality and computational efficiency. In this paper, we propose an efficient image mosaicing algorithm for large area visual mapping in underwater environments using multiple underwater robots. Our method identifies overlapping image pairs in the trajectories carried out by the different robots during the topology estimation process, being this a cornerstone for efficiently mapping large areas of the seafloor. We present comparative results based on challenging real underwater datasets, which simulated multi-robot mapping

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2012R1A1A1015307) and partly by the Human Resources Development program (No. 20134030200300) of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government Ministry of Trade, Industry and Energy. It was also partially funded through European Union projects FP7-ICT-2011-288704 (MORPH) and FP7-312762 (EUROFLEETS2) as well as under grant CTM2010-15216 (MuMap) from the Spanish Ministry of Science and Innovation (MCINN)

© Pattern Recognition Letters, 2014, vol. 46, p. 20-26

Elsevier

Author: Elibol, Armagan
Kim, Jinwhan
Grácias, Nuno Ricardo Estrela
García Campos, Rafael
Date: 2014
Abstract: Robotic platforms have advanced greatly in terms of their remote sensing capabilities, including obtaining optical information using cameras. Alongside these advances, visual mapping has become a very active research area, which facilitates the mapping of areas inaccessible to humans. This requires the efficient processing of data to increase the final mosaic quality and computational efficiency. In this paper, we propose an efficient image mosaicing algorithm for large area visual mapping in underwater environments using multiple underwater robots. Our method identifies overlapping image pairs in the trajectories carried out by the different robots during the topology estimation process, being this a cornerstone for efficiently mapping large areas of the seafloor. We present comparative results based on challenging real underwater datasets, which simulated multi-robot mapping
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2012R1A1A1015307) and partly by the Human Resources Development program (No. 20134030200300) of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government Ministry of Trade, Industry and Energy. It was also partially funded through European Union projects FP7-ICT-2011-288704 (MORPH) and FP7-312762 (EUROFLEETS2) as well as under grant CTM2010-15216 (MuMap) from the Spanish Ministry of Science and Innovation (MCINN)
Format: application/pdf
ISSN: 0167-8655
Document access: http://hdl.handle.net/10256/10321
Language: eng
Publisher: Elsevier
Collection: MICINN/PN 2011-2014/CTM2010-15216
Reproducció digital del document publicat a: http://dx.doi.org/10.1016/j.patrec.2014.04.020
Articles publicats (D-ATC)
info:eu-repo/grantAgreement/EC/FP7/312762
info:eu-repo/grantAgreement/EC/FP7/288704
Is part of: © Pattern Recognition Letters, 2014, vol. 46, p. 20-26
Rights: Tots els drets reservats
Subject: Visió per ordinador
Computer vision
Imatges -- Segmentació
Image processing
Vehicles submergibles
Submersibles
Robots mòbils
Mobile robots
Title: Efficient image mosaicing for multi-robot visual underwater mapping
Type: info:eu-repo/semantics/article
Repository: DUGiDocs

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