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Authors: D. Di Mauro 1 ; A. Furnari 1 ; G. Patanè 2 ; S. Battiato 1 and G. M. Farinella 1

Affiliations: 1 Department of Mathematics and Computer Science, University of Catania, Catania and Italy ; 2 Park Smart s.r.l., Catania and Italy

Keyword(s): Counting, Deep Learning, Classification, Object Detection, Smart Cities.

Related Ontology Subjects/Areas/Topics: Multimedia ; Multimedia Signal Processing ; Neural Networks, Spiking Systems, Genetic Algorithms and Fuzzy Logic ; Telecommunications

Abstract: The world-wide growth of population in urban areas demands for the development of sustainable technologies to manage city services, such as transportation, in an efficient way. Motivated by the cost-effectiveness of image-based solutions, in this paper we investigate the exploitation of techniques based on image classification and object detection to count cars and non-empty stalls in parking areas. The analysis is performed on a dataset of images collected in a real parking area. Results show that techniques based on image classification are very effective when parking stalls are delimited by marking lines and the geometry of the scene is known in advance.

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Paper citation in several formats:
Di Mauro, D., Furnari, A., Patanè, G., Battiato, S. and M. Farinella, G. (2018). A Comparison of Techniques based on Image Classification and Object Detection to Count Cars and Non-empty Stalls in Parking Spaces. In Proceedings of the 15th International Joint Conference on e-Business and Telecommunications - ICETE; ISBN 978-989-758-319-3; ISSN 2184-3236, SciTePress, pages 328-336. DOI: 10.5220/0006851404940502

@conference{icete18,
author={D. {Di Mauro} and A. Furnari and G. Patanè and S. Battiato and G. {M. Farinella}},
title={A Comparison of Techniques based on Image Classification and Object Detection to Count Cars and Non-empty Stalls in Parking Spaces},
booktitle={Proceedings of the 15th International Joint Conference on e-Business and Telecommunications - ICETE},
year={2018},
pages={328-336},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006851404940502},
isbn={978-989-758-319-3},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on e-Business and Telecommunications - ICETE
TI - A Comparison of Techniques based on Image Classification and Object Detection to Count Cars and Non-empty Stalls in Parking Spaces
SN - 978-989-758-319-3
IS - 2184-3236
AU - Di Mauro, D.
AU - Furnari, A.
AU - Patanè, G.
AU - Battiato, S.
AU - M. Farinella, G.
PY - 2018
SP - 328
EP - 336
DO - 10.5220/0006851404940502
PB - SciTePress

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