Sleepy Eye's Recognition for Drowsiness Detection

With the progress of science technology and the vehicle industry, there are more and more vehicles on the road. As a result, the heavy traffic often leads to more and more traffic accidents. In common traffic accident, the driver's inattention is usually a main reason. To avoid this situation,...

Full description

Saved in:
Bibliographic Details
Published in2013 International Symposium on Biometrics and Security Technologies pp. 176 - 179
Main Authors Lin, Shinfeng D., Jia-Jen Lin, Chin-Yao Chung
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2013
Subjects
Drowsiness
Eye's State
Face
Face detection
Feature extraction
Image edge detection
Support vector machines
Training
Vehicles
Online AccessGet full text

Cover

More Information
Summary:With the progress of science technology and the vehicle industry, there are more and more vehicles on the road. As a result, the heavy traffic often leads to more and more traffic accidents. In common traffic accident, the driver's inattention is usually a main reason. To avoid this situation, this paper proposes a sleepy eye's recognition system for drowsiness detection. First, a cascaded Adaboost classifier with the Haar-like features is utilized to find out the face region. Second, the eyes region is located by Active Shape Models(ASM) search algorithm. Then the binary pattern and edge detection are adopted to extract the eyes feature and determine the eye's state. Experimental results demonstrate the comparative performance, even without the training stage, with other methods.
DOI:10.1109/ISBAST.2013.31