Drowsiness Detection based on Video Analysis Approach

Belhassen Akrout, Walid Mahdi, Abdelmajid Ben Hamadou

Abstract

The lack of concentration due to the driver fatigue is a major cause that justifies the high number of accidents. This article describes a new approach to detect reduced alertness automatically from a system based on video analysis, to prevent the driver and also to reduce the number of accidents. Our approach is based on the temporal analysis of the state of opening and closing the eyes. Unlike many other works, our approach is based only on the analysis of geometric features captured form faces video sequence and does not need any elements linked to the human being.

References

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Paper Citation


in Harvard Style

Akrout B., Mahdi W. and Ben Hamadou A. (2013). Drowsiness Detection based on Video Analysis Approach . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-47-1, pages 413-416. DOI: 10.5220/0004210004130416


in Bibtex Style

@conference{visapp13,
author={Belhassen Akrout and Walid Mahdi and Abdelmajid Ben Hamadou},
title={Drowsiness Detection based on Video Analysis Approach},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={413-416},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004210004130416},
isbn={978-989-8565-47-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)
TI - Drowsiness Detection based on Video Analysis Approach
SN - 978-989-8565-47-1
AU - Akrout B.
AU - Mahdi W.
AU - Ben Hamadou A.
PY - 2013
SP - 413
EP - 416
DO - 10.5220/0004210004130416