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Authors: Danilo Avola 1 ; Marco Bernardi 2 ; Luigi Cinque 2 ; Gian Luca Foresti 1 and Cristiano Massaroni 2

Affiliations: 1 University of Udine, Italy ; 2 Sapienza University, Italy

ISBN: 978-989-758-276-9

ISSN: 2184-4313

Keyword(s): Foreground Detection, Keypoint Clustering, Neural Background Subtraction, Moving Objects, PTZ Cameras.

Related Ontology Subjects/Areas/Topics: Clustering ; Pattern Recognition ; Theory and Methods

Abstract: Detection of moving objects is a topic of great interest in computer vision. This task represents a prerequisite for more complex duties, such as classification and re-identification. One of the main challenges regards the management of dynamic factors, with particular reference to bootstrapping and illumination change issues. The recent widespread of PTZ cameras has made these issues even more complex in terms of performance due to their composite movements (i.e., pan, tilt, and zoom). This paper proposes a combined keypoint clustering and neural background subtraction method for real-time moving object detection in video sequences acquired by PTZ cameras. Initially, the method performs a spatio-temporal tracking of the sets of moving keypoints to recognize the foreground areas and to establish the background. Subsequently, it adopts a neural background subtraction to accomplish a foreground detection, in these areas, able to manage bootstrapping and gradual illumination cha nges. Experimental results on two well-known public datasets and comparisons with different key works of the current state-of-the-art demonstrate the remarkable results of the proposed method. (More)

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Paper citation in several formats:
Avola, D.; Bernardi, M.; Cinque, L.; Foresti, G. and Massaroni, C. (2018). Combining Keypoint Clustering and Neural Background Subtraction for Real-time Moving Object Detection by PTZ Cameras.In Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-276-9, ISSN 2184-4313, pages 638-645. DOI: 10.5220/0006722506380645

@conference{icpram18,
author={Danilo Avola. and Marco Bernardi. and Luigi Cinque. and Gian Luca Foresti. and Cristiano Massaroni.},
title={Combining Keypoint Clustering and Neural Background Subtraction for Real-time Moving Object Detection by PTZ Cameras},
booktitle={Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2018},
pages={638-645},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006722506380645},
isbn={978-989-758-276-9},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Combining Keypoint Clustering and Neural Background Subtraction for Real-time Moving Object Detection by PTZ Cameras
SN - 978-989-758-276-9
AU - Avola, D.
AU - Bernardi, M.
AU - Cinque, L.
AU - Foresti, G.
AU - Massaroni, C.
PY - 2018
SP - 638
EP - 645
DO - 10.5220/0006722506380645

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