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Article

An Augmented Reality Periscope for Submarines with Extended Visual Classification

Instituto de Computação, Universidade Federal Fluminense (UFF), Av. Gal. Milton Tavares de Souza, Niterói 24210-346, RJ, Brazil
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Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editors: Andrea Sanna, Federico Manuri and Francesco De Pace
Sensors 2021, 21(22), 7624; https://doi.org/10.3390/s21227624
Received: 30 September 2021 / Revised: 4 November 2021 / Accepted: 4 November 2021 / Published: 17 November 2021
(This article belongs to the Topic Augmented and Mixed Reality)
Submarines are considered extremely strategic for any naval army due to their stealth capability. Periscopes are crucial sensors for these vessels, and emerging to the surface or periscope depth is required to identify visual contacts through this device. This maneuver has many procedures and usually has to be fast and agile to avoid exposure. This paper presents and implements a novel architecture for real submarine periscopes developed for future Brazilian naval fleet operations. Our system consists of a probe that is connected to the craft and carries a 360 camera. We project and take the images inside the vessel using traditional VR/XR devices. We also propose and implement an efficient computer vision-based MR technique to estimate and display detected vessels effectively and precisely. The vessel detection model is trained using synthetic images. So, we built and made available a dataset composed of 99,000 images. Finally, we also estimate distances of the classified elements, showing all the information in an AR-based interface. Although the probe is wired-connected, it allows for the vessel to stand in deep positions, reducing its exposure and introducing a new way for submarine maneuvers and operations. We validate our proposal through a user experience experiment using 19 experts in periscope operations. View Full-Text
Keywords: computer vision; deep learning; mixed reality; object detection; periscope; synthetic data; submarine; transfer learning computer vision; deep learning; mixed reality; object detection; periscope; synthetic data; submarine; transfer learning
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MDPI and ACS Style

Breitinger, A.; Clua, E.; Fernandes, L.A.F. An Augmented Reality Periscope for Submarines with Extended Visual Classification. Sensors 2021, 21, 7624. https://doi.org/10.3390/s21227624

AMA Style

Breitinger A, Clua E, Fernandes LAF. An Augmented Reality Periscope for Submarines with Extended Visual Classification. Sensors. 2021; 21(22):7624. https://doi.org/10.3390/s21227624

Chicago/Turabian Style

Breitinger, André, Esteban Clua, and Leandro A. F. Fernandes. 2021. "An Augmented Reality Periscope for Submarines with Extended Visual Classification" Sensors 21, no. 22: 7624. https://doi.org/10.3390/s21227624

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