Authors:
Filippo L. M. Milotta
1
;
Antonino Furnari
1
;
Sebastiano Battiato
1
;
Maria De Salvo
2
;
Giovanni M. Signorello
2
and
Giovanni M. Farinella
3
Affiliations:
1
University of Catania, Department of Mathematics and Computer Science, Via Santa Sofia - 64, Catania 95125 and Italy
;
2
University of Catania, CUTGANA, Viale A. Doria 6, Catania 95123 and Italy
;
3
University of Catania, Department of Mathematics and Computer Science, Via Santa Sofia - 64, Catania 95125, Italy, University of Catania, CUTGANA, Viale A. Doria 6, Catania 95123 and Italy
Keyword(s):
Egocentric (First Person) Vision, Localization, GPS, Multimodal Data Fusion.
Abstract:
Localization in outdoor contexts such as parks and natural reserves can be used to augment the visitors’ experience and to provide the site manager with valid analytics to improve the fruition of the site. In this paper, we address the problem of visitors localization in natural sites by exploiting both egocentric vision and GPS data. To this aim, we gathered a dataset of first person videos in the Botanical Garden of the University of Catania. Along with the videos, we also acquired GPS coordinates. The data have been acquired by 12 different users, each walking all around the garden for an average of 30 minutes (i.e., a total of about 6 hours of recording). Using the collected dataset, we show that localizing visitors based solely on GPS data is not sufficient to understand the location of the visitors in a natural site. We hence investigate how to exploit visual data to perform localization by casting the problem as the one of classifying images among the different contexts of the
natural site. Our investigation highlights that visual information can be leveraged to achieve better localization and that Egocentric Vision and GPS can be exploited jointly to improve accuracy.
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