AU measurements from cascaded Adaboost for driver drowsiness detection

Author

Yee Koon Loh ; Suandi, Shahrel A.

Author_Institution

Intell. Biometric Group, Univ. Sains Malaysia, Nibong Tebal, Malaysia

fYear

2013

fDate

19-21 June 2013

Firstpage

573

Lastpage

576

Abstract

Driver fatigue has getting more attentions from researchers. One of the methods to recognize driver fatigue is by monitoring driver´s facial expression. Facial Action Coding System (FACS) is well-known in facial behavior sciences and Action Unit (AU) is used as the measurement. In this work, AU coded facial image is represented by Gabor filters in different orientations and frequencies, which are classified into respective classes using cascaded AdaBoost. The result is validated with ground truth information given in the database. Results show the validation of AU measurement in computer vision method and will be further applied in driver monitoring system to predict the driver´s fatigue level.

Keywords

Gabor filters; computer vision; face recognition; image coding; image representation; learning (artificial intelligence); object detection; traffic engineering computing; AU coded facial image representation; AU measurements; FACS; Gabor filters; action unit; cascaded Adaboost; computer vision method; driver drowsiness detection; driver facial expression monitoring; driver fatigue recognition; driver monitoring system; facial action coding system; facial behavior sciences; ground truth information; Computational modeling; Face; Fatigue; Feature extraction; Gold; Monitoring; Vehicles; AU measurement; AdaBoost; Driver fatigue; Gabor filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Applications (ICIEA), 2013 8th IEEE Conference on

Conference_Location

Melbourne, VIC

Print_ISBN

978-1-4673-6320-4

Type

conf

DOI

10.1109/ICIEA.2013.6566434

Filename

6566434