Vision based approach for driver drowsiness detection based on 3D head orientation

Belhassen Akrout; Walid Mahdi

doi:10.1007/978-94-007-6738-6_6

Vision based approach for driver drowsiness detection based on 3D head orientation

Belhassen Akrout, Walid Mahdi

University of Sfax

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

The increasing number of accidents is attributed to several factors, among which is the lack of concentration caused by fatigue. The driver drowsiness state can be detected with several ways. Among these methods, we can quote those which analyze the driver eyes or head by video or studying the EEG signal. We present, in this paper an approach which makes it possible to determine the orientation of the driver head to capture the drowsiness state. This approach is based on the estimation of head rotation angles in the three directions yaw, pitch and roll by exploiting only three points face features.

Original language	English
Title of host publication	Multimedia and Ubiquitous Engineering, MUE 2013
Pages	43-50
Number of pages	8
DOIs	https://doi.org/10.1007/978-94-007-6738-6_6
State	Published - 2013
Externally published	Yes
Event	FTRA 7th International Conference on Multimedia and Ubiquitous Engineering, MUE 2013 - Seoul, Korea, Republic of Duration: 9 May 2013 → 11 May 2013

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	240 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	FTRA 7th International Conference on Multimedia and Ubiquitous Engineering, MUE 2013
Country/Territory	Korea, Republic of
City	Seoul
Period	9/05/13 → 11/05/13

Keywords

3D head orientation
Driver drowsiness detection
Haar features
Harris detector
Perspective Projection

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-94-007-6738-6_6

Cite this

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title = "Vision based approach for driver drowsiness detection based on 3D head orientation",

abstract = "The increasing number of accidents is attributed to several factors, among which is the lack of concentration caused by fatigue. The driver drowsiness state can be detected with several ways. Among these methods, we can quote those which analyze the driver eyes or head by video or studying the EEG signal. We present, in this paper an approach which makes it possible to determine the orientation of the driver head to capture the drowsiness state. This approach is based on the estimation of head rotation angles in the three directions yaw, pitch and roll by exploiting only three points face features.",

keywords = "3D head orientation, Driver drowsiness detection, Haar features, Harris detector, Perspective Projection",

author = "Belhassen Akrout and Walid Mahdi",

year = "2013",

doi = "10.1007/978-94-007-6738-6\_6",

language = "English",

isbn = "9789400767379",

series = "Lecture Notes in Electrical Engineering",

pages = "43--50",

booktitle = "Multimedia and Ubiquitous Engineering, MUE 2013",

note = "FTRA 7th International Conference on Multimedia and Ubiquitous Engineering, MUE 2013 ; Conference date: 09-05-2013 Through 11-05-2013",

}

Akrout, B & Mahdi, W 2013, Vision based approach for driver drowsiness detection based on 3D head orientation. in Multimedia and Ubiquitous Engineering, MUE 2013. Lecture Notes in Electrical Engineering, vol. 240 LNEE, pp. 43-50, FTRA 7th International Conference on Multimedia and Ubiquitous Engineering, MUE 2013, Seoul, Korea, Republic of, 9/05/13. https://doi.org/10.1007/978-94-007-6738-6_6

TY - GEN

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AU - Akrout, Belhassen

AU - Mahdi, Walid

PY - 2013

Y1 - 2013

N2 - The increasing number of accidents is attributed to several factors, among which is the lack of concentration caused by fatigue. The driver drowsiness state can be detected with several ways. Among these methods, we can quote those which analyze the driver eyes or head by video or studying the EEG signal. We present, in this paper an approach which makes it possible to determine the orientation of the driver head to capture the drowsiness state. This approach is based on the estimation of head rotation angles in the three directions yaw, pitch and roll by exploiting only three points face features.

AB - The increasing number of accidents is attributed to several factors, among which is the lack of concentration caused by fatigue. The driver drowsiness state can be detected with several ways. Among these methods, we can quote those which analyze the driver eyes or head by video or studying the EEG signal. We present, in this paper an approach which makes it possible to determine the orientation of the driver head to capture the drowsiness state. This approach is based on the estimation of head rotation angles in the three directions yaw, pitch and roll by exploiting only three points face features.

KW - 3D head orientation

KW - Driver drowsiness detection

KW - Haar features

KW - Harris detector

KW - Perspective Projection

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DO - 10.1007/978-94-007-6738-6_6

M3 - Conference contribution

AN - SCOPUS:84880746579

SN - 9789400767379

T3 - Lecture Notes in Electrical Engineering

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BT - Multimedia and Ubiquitous Engineering, MUE 2013

T2 - FTRA 7th International Conference on Multimedia and Ubiquitous Engineering, MUE 2013

Y2 - 9 May 2013 through 11 May 2013

ER -

Vision based approach for driver drowsiness detection based on 3D head orientation

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

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