Vehicle Tracking based on Customized Template Matching

Sebastiano Battiato, Giovanni Maria Farinella, Antonino Furnari, Giovanni Puglisi, Anique Snijders, Jelmer Spiekstra

Abstract

In this paper we present a template matching based vehicle tracking algorithm designed for traffic analysis purposes. The proposed approach could be integrated in a system able to understand lane changes, gate passages and other behaviours useful for traffic analysis. After reviewing some state-of-the-art object tracking techniques, the proposed approach is presented as a customization of the template matching algorithm by introducing different modules designed to solve specific issues of the application context. The experiments are performed on a dataset compound by real-world cases of vehicle traffic acquired in different scene contexts (e.g., highway, urban, etc.) and weather conditions (e.g., raining, snowing, etc.). The performances of the proposed approach are compared with respect to a baseline technique based on background-foreground separation.

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Paper Citation


in Harvard Style

Battiato S., Farinella G., Furnari A., Puglisi G., Snijders A. and Spiekstra J. (2014). Vehicle Tracking based on Customized Template Matching . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: PANORAMA, (VISIGRAPP 2014) ISBN 978-989-758-004-8, pages 755-760. DOI: 10.5220/0004872607550760


in Bibtex Style

@conference{panorama14,
author={Sebastiano Battiato and Giovanni Maria Farinella and Antonino Furnari and Giovanni Puglisi and Anique Snijders and Jelmer Spiekstra},
title={Vehicle Tracking based on Customized Template Matching},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: PANORAMA, (VISIGRAPP 2014)},
year={2014},
pages={755-760},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004872607550760},
isbn={978-989-758-004-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: PANORAMA, (VISIGRAPP 2014)
TI - Vehicle Tracking based on Customized Template Matching
SN - 978-989-758-004-8
AU - Battiato S.
AU - Farinella G.
AU - Furnari A.
AU - Puglisi G.
AU - Snijders A.
AU - Spiekstra J.
PY - 2014
SP - 755
EP - 760
DO - 10.5220/0004872607550760