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Authors: Massimo Magrini ; Davide Moroni ; Gabriele Pieri and Ovidio Salvetti

Affiliation: Institute of Information Science and Technologies - CNR, Italy

Keyword(s): Real-time Imaging, Embedded Systems, Intelligent Transport Systems (ITS).

Related Ontology Subjects/Areas/Topics: Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Pervasive Smart Cameras

Abstract: Nowadays pervasive monitoring of traffic flows in urban environment is a topic of great relevance, since the information it is possible to gather may be exploited for a more efficient and sustainable mobility. In this paper, we address the use of smart cameras for assessing the level of service of roads and early detect possible congestion. In particular, we devise a lightweight method that is suitable for use on low power and low cost sensors, resulting in a scalable and sustainable approach to flow monitoring over large areas. We also present the current prototype of an ad hoc device we designed and report experimental results obtained during a field test.

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Paper citation in several formats:
Magrini, M.; Moroni, D.; Pieri, G. and Salvetti, O. (2015). Lightweight Computer Vision Methods for Traffic Flow Monitoring on Low Power Embedded Sensors. In Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: MMS-ER3D; ISBN 978-989-758-090-1; ISSN 2184-4321, SciTePress, pages 663-670. DOI: 10.5220/0005361006630670

@conference{mms-er3d15,
author={Massimo Magrini. and Davide Moroni. and Gabriele Pieri. and Ovidio Salvetti.},
title={Lightweight Computer Vision Methods for Traffic Flow Monitoring on Low Power Embedded Sensors},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: MMS-ER3D},
year={2015},
pages={663-670},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005361006630670},
isbn={978-989-758-090-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: MMS-ER3D
TI - Lightweight Computer Vision Methods for Traffic Flow Monitoring on Low Power Embedded Sensors
SN - 978-989-758-090-1
IS - 2184-4321
AU - Magrini, M.
AU - Moroni, D.
AU - Pieri, G.
AU - Salvetti, O.
PY - 2015
SP - 663
EP - 670
DO - 10.5220/0005361006630670
PB - SciTePress

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