Image Based Localization with Simulated Egocentric Navigations

Santi A. Orlando; Antonino Furnari; Sebastiano Battiato; Giovanni M. Farinella

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Paper

Image Based Localization with Simulated Egocentric Navigations

Topics: Content-Based Indexing, Search, and Retrieval; Deep Learning for Visual Understanding ; First Person (Egocentric) Vision ; Machine Learning Technologies for Vision

In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5 VISAPP: VISAPP, 305-312, 2019 , Prague, Czech Republic

Authors: Santi A. Orlando ¹ ; Antonino Furnari ² ; Sebastiano Battiato ² and Giovanni M. Farinella ²

Affiliations: ¹ Department of Mathematics and Computer Science, University of Catania, Catania, Italy, DWORD - Xenia Progetti s.r.l., Acicastello, Catania and Italy ; ² Department of Mathematics and Computer Science, University of Catania, Catania and Italy

Keyword(s): Image-Based Localization, Similarity Search, Metric Learning, Simulated Data.

Abstract: Current methods for Image-Based Localization (IBL) require the collection and labelling of large datasets of images or videos for training purpose. Such procedure generally requires a significant effort, involving the use of dedicated sensors or the employment of structure from motion techniques. To overcome the difficulties of acquiring a dataset suitable to train models to study IBL, we propose a tool to generate simulated egocentric data starting from 3D models of real indoor environments. The generated data are automatically associated to the 3D camera pose information to be exploited during training, hence avoiding the need to perform “manual” labelling. To asses the effectiveness of the proposed tool, we generate and release a huge dataset of egocentric images using a 3D model of a real environment belonging to the S3DIS dataset. We also perform a benchmark study for 3 Degrees of Freedom (3DoF) indoor localization by considering an IBL pipeline based on image-retrieval and a tr iplet network. Results highlight that the generated dataset is useful to study the IBL problem and allows to perform experiments with different settings in a simple way. (More)

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Paper citation in several formats:

Orlando, S. A., Furnari, A., Battiato, S. and Farinella, G. M. (2019). Image Based Localization with Simulated Egocentric Navigations. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP; ISBN 978-989-758-354-4; ISSN 2184-4321, SciTePress, pages 305-312. DOI: 10.5220/0007356503050312

@conference{visapp19,
author={Santi A. Orlando and Antonino Furnari and Sebastiano Battiato and Giovanni M. Farinella},
title={Image Based Localization with Simulated Egocentric Navigations},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP},
year={2019},
pages={305-312},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007356503050312},
isbn={978-989-758-354-4},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP
TI - Image Based Localization with Simulated Egocentric Navigations
SN - 978-989-758-354-4
IS - 2184-4321
AU - Orlando, S.
AU - Furnari, A.
AU - Battiato, S.
AU - Farinella, G.
PY - 2019
SP - 305
EP - 312
DO - 10.5220/0007356503050312
PB - SciTePress