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Authors: Kristof Van Beeck and Toon Goedemé

Affiliation: Campus De Nayer - KU Leuven and KU Leuven, Belgium

ISBN: 978-989-758-018-5

Keyword(s): Pedestrian Detection, Tracking, Real-time, Computer Vision, Active Safety Systems.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Human-Computer Interaction ; Image and Video Analysis ; Image Understanding ; Methodologies and Methods ; Motion and Tracking ; Motion, Tracking and Stereo Vision ; Object Recognition ; Pattern Recognition ; Physiological Computing Systems ; Software Engineering ; Video Analysis

Abstract: In this paper we present a multi-pedestrian detection and tracking framework targeting a specific application: detecting vulnerable road users in a truck’s blind spot zone. Research indicates that existing non-vision based safety solutions are not able to handle this problem completely. Therefore we aim to develop an active safety system which warns the truck driver if pedestrians are present in the truck’s blind spot zone. Our system solely uses the vision input from the truck’s blind spot camera to detect pedestrians. This is not a trivial task, since the application inherently requires real-time operation while at the same time attaining very high accuracy. Furthermore we need to cope with the large lens distortion and the extreme viewpoints introduced by the blind spot camera. To achieve this, we propose a fast and efficient pedestrian detection and tracking framework based on our novel perspective warping window approach. To evaluate our algorithm we recorded several realisticall y simulated blind spot scenarios with a genuine blind spot camera mounted on a real truck. We show that our algorithm achieves excellent accuracy results at real-time performance, using a single core CPU implementation only. (More)

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Paper citation in several formats:
Van Beeck, K. and Goedemé, T. (2014). Real-time Pedestrian Detection in a Truck’s Blind Spot Camera.In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-018-5, pages 412-420. DOI: 10.5220/0004821304120420

@conference{icpram14,
author={Kristof Van Beeck. and Toon Goedemé.},
title={Real-time Pedestrian Detection in a Truck’s Blind Spot Camera},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2014},
pages={412-420},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004821304120420},
isbn={978-989-758-018-5},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Real-time Pedestrian Detection in a Truck’s Blind Spot Camera
SN - 978-989-758-018-5
AU - Van Beeck, K.
AU - Goedemé, T.
PY - 2014
SP - 412
EP - 420
DO - 10.5220/0004821304120420

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