Cart (Loading....) | Create Account
Close category search window
 

Drowsiness Recognition Using the Least Correlated LBPH

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Cheng-Chang Lien ; Dept. Comput. Sci. & Inf. Eng., Chung Hua Univ., Hsinchu, Taiwan ; Pei-Rong Lin

In recent years, the drowsiness recognition is widely applied to the driver alerting or distance learning. The drowsiness recognition system is constructed on the basis of the recognition of eye states. The conventional methods for recognizing the eye states are often influenced by the illumination variations or hair/glasses occlusion. In this paper, we propose a new image feature called "least correlated LBP histogram (LC-LBPH)" to generate a high discriminate image features for recognizing the eye states robustly. Then, the method of independent component analysis (ICA) is applied to derive the low-dimensional and statistical independent feature vectors. Finally, support vector machines (SVM) are trained to recognize the eye states. Furthermore, we design four rules to classify three eye transition patterns which define the normal (consciousness), drowsiness, and sleeping situations. Experimental results show that the eye-state recognition rate is about 0.08 seconds per frame and the drowsiness recognition accuracy approaches 98%.

Published in:

Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2012 Eighth International Conference on

Date of Conference:

18-20 July 2012

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.