Yawning detection by the analysis of variational descriptor for monitoring driver drowsiness

Belhassen Akrout; Walid Mahdi

doi:10.1109/IPAS.2016.7880127

Yawning detection by the analysis of variational descriptor for monitoring driver drowsiness

Belhassen Akrout
, Walid Mahdi

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

39 Scopus citations

Abstract

The road safety is a problem which was approached by several countries following a big raise of the number of accidents. The drowsiness represents one among the causes of the road accidents. The accidents related to the drowsiness often occur on the highways, but also on the main roads, even inside the localities. Today, it is possible to detect the state of tiredness of the driver with the development of the technology of the computer vision. The results of research in physiology show that the first level of lack of vigilance appears by an increase in the frequency of the yawn. In this work, we propose a novel approach for yawning detection for monitoring driver fatigue. In fact, our approach rests on the study of the spatio-Temporal descriptors of a nonstationary and non-linear signal. This approach is evaluated by both YawDD [1] and our MiraclHB [2] databases. The evaluation shows many promising results and shows the effectiveness of the suggested approach.

Original language	English
Title of host publication	IPAS 2016 - 2nd International Image Processing, Applications and Systems Conference
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509016457
DOIs	https://doi.org/10.1109/IPAS.2016.7880127
State	Published - 16 Mar 2017
Externally published	Yes
Event	2nd International Image Processing, Applications and Systems Conference, IPAS 2016 - Hammamet, Tunisia Duration: 5 Nov 2016 → 7 Nov 2016

Publication series

Name	IPAS 2016 - 2nd International Image Processing, Applications and Systems Conference

Conference

Conference	2nd International Image Processing, Applications and Systems Conference, IPAS 2016
Country/Territory	Tunisia
City	Hammamet
Period	5/11/16 → 7/11/16

UN SDGs

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

SDG 3 Good Health and Well-being
SDG 11 Sustainable Cities and Communities

Keywords

Driver drowsiness detection
Human safety
Intelligent vehicle
Yawning detection

Access to Document

10.1109/IPAS.2016.7880127

Cite this

Akrout, B., & Mahdi, W. (2017). Yawning detection by the analysis of variational descriptor for monitoring driver drowsiness. In IPAS 2016 - 2nd International Image Processing, Applications and Systems Conference Article 7880127 (IPAS 2016 - 2nd International Image Processing, Applications and Systems Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IPAS.2016.7880127

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title = "Yawning detection by the analysis of variational descriptor for monitoring driver drowsiness",

abstract = "The road safety is a problem which was approached by several countries following a big raise of the number of accidents. The drowsiness represents one among the causes of the road accidents. The accidents related to the drowsiness often occur on the highways, but also on the main roads, even inside the localities. Today, it is possible to detect the state of tiredness of the driver with the development of the technology of the computer vision. The results of research in physiology show that the first level of lack of vigilance appears by an increase in the frequency of the yawn. In this work, we propose a novel approach for yawning detection for monitoring driver fatigue. In fact, our approach rests on the study of the spatio-Temporal descriptors of a nonstationary and non-linear signal. This approach is evaluated by both YawDD [1] and our MiraclHB [2] databases. The evaluation shows many promising results and shows the effectiveness of the suggested approach.",

keywords = "Driver drowsiness detection, Human safety, Intelligent vehicle, Yawning detection",

author = "Belhassen Akrout and Walid Mahdi",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2nd International Image Processing, Applications and Systems Conference, IPAS 2016 ; Conference date: 05-11-2016 Through 07-11-2016",

year = "2017",

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doi = "10.1109/IPAS.2016.7880127",

language = "English",

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Akrout, B & Mahdi, W 2017, Yawning detection by the analysis of variational descriptor for monitoring driver drowsiness. in IPAS 2016 - 2nd International Image Processing, Applications and Systems Conference., 7880127, IPAS 2016 - 2nd International Image Processing, Applications and Systems Conference, Institute of Electrical and Electronics Engineers Inc., 2nd International Image Processing, Applications and Systems Conference, IPAS 2016, Hammamet, Tunisia, 5/11/16. https://doi.org/10.1109/IPAS.2016.7880127

Yawning detection by the analysis of variational descriptor for monitoring driver drowsiness. / Akrout, Belhassen; Mahdi, Walid.
IPAS 2016 - 2nd International Image Processing, Applications and Systems Conference. Institute of Electrical and Electronics Engineers Inc., 2017. 7880127 (IPAS 2016 - 2nd International Image Processing, Applications and Systems Conference).

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

TY - GEN

T1 - Yawning detection by the analysis of variational descriptor for monitoring driver drowsiness

AU - Akrout, Belhassen

AU - Mahdi, Walid

PY - 2017/3/16

Y1 - 2017/3/16

N2 - The road safety is a problem which was approached by several countries following a big raise of the number of accidents. The drowsiness represents one among the causes of the road accidents. The accidents related to the drowsiness often occur on the highways, but also on the main roads, even inside the localities. Today, it is possible to detect the state of tiredness of the driver with the development of the technology of the computer vision. The results of research in physiology show that the first level of lack of vigilance appears by an increase in the frequency of the yawn. In this work, we propose a novel approach for yawning detection for monitoring driver fatigue. In fact, our approach rests on the study of the spatio-Temporal descriptors of a nonstationary and non-linear signal. This approach is evaluated by both YawDD [1] and our MiraclHB [2] databases. The evaluation shows many promising results and shows the effectiveness of the suggested approach.

AB - The road safety is a problem which was approached by several countries following a big raise of the number of accidents. The drowsiness represents one among the causes of the road accidents. The accidents related to the drowsiness often occur on the highways, but also on the main roads, even inside the localities. Today, it is possible to detect the state of tiredness of the driver with the development of the technology of the computer vision. The results of research in physiology show that the first level of lack of vigilance appears by an increase in the frequency of the yawn. In this work, we propose a novel approach for yawning detection for monitoring driver fatigue. In fact, our approach rests on the study of the spatio-Temporal descriptors of a nonstationary and non-linear signal. This approach is evaluated by both YawDD [1] and our MiraclHB [2] databases. The evaluation shows many promising results and shows the effectiveness of the suggested approach.

KW - Driver drowsiness detection

KW - Human safety

KW - Intelligent vehicle

KW - Yawning detection

UR - https://www.scopus.com/pages/publications/85018573202

U2 - 10.1109/IPAS.2016.7880127

DO - 10.1109/IPAS.2016.7880127

M3 - Conference contribution

AN - SCOPUS:85018573202

T3 - IPAS 2016 - 2nd International Image Processing, Applications and Systems Conference

BT - IPAS 2016 - 2nd International Image Processing, Applications and Systems Conference

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd International Image Processing, Applications and Systems Conference, IPAS 2016

Y2 - 5 November 2016 through 7 November 2016

ER -

Akrout B, Mahdi W. Yawning detection by the analysis of variational descriptor for monitoring driver drowsiness. In IPAS 2016 - 2nd International Image Processing, Applications and Systems Conference. Institute of Electrical and Electronics Engineers Inc. 2017. 7880127. (IPAS 2016 - 2nd International Image Processing, Applications and Systems Conference). doi: 10.1109/IPAS.2016.7880127

Yawning detection by the analysis of variational descriptor for monitoring driver drowsiness

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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