This article presents a real-time mosaicking algorithm based on a SLAM framework. The mosaic of the seafloor can be useful in real time for a ROV operator that is piloting the ROV. Two important aspects arise in this kind of work: data association and computational time. In order to solve the first one, a combination of SURF features and template correlation methods is used. To minimize the computational time, a very recent approach in the domain of feature description is used: BRIEF binary features. Finally, to be able to update the whole mosaicking in a fast and easy way, local mosaics are used instead of a global one. The algorithm was tested using data collected in a typical experiment and the results show the improvement with respect to previous versions of a similar algorithm. © 2013 IEEE.

A real-time mosaicking algorithm using binary features for ROVs

Veruggio Gianmarco;Caccia Massimo;Zereik Enrica;Bruzzone Gabriele
2013

Abstract

This article presents a real-time mosaicking algorithm based on a SLAM framework. The mosaic of the seafloor can be useful in real time for a ROV operator that is piloting the ROV. Two important aspects arise in this kind of work: data association and computational time. In order to solve the first one, a combination of SURF features and template correlation methods is used. To minimize the computational time, a very recent approach in the domain of feature description is used: BRIEF binary features. Finally, to be able to update the whole mosaicking in a fast and easy way, local mosaics are used instead of a global one. The algorithm was tested using data collected in a typical experiment and the results show the improvement with respect to previous versions of a similar algorithm. © 2013 IEEE.
2013
Istituto di Studi sui Sistemi Intelligenti per l'Automazione - ISSIA - Sede Bari
9781479909971
SLAM (robots)
autonomous underwater vehicles
correlation theory
feature extraction
image segmentation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/276521
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