Efficient measurement of the eye blinking by using decision function for intelligent vehicles

Ilkwon Park, Jung Ho Ahn, Hyeran Byun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)


In this paper, we propose an efficient measurement of the eye blinking for drowsy driver detection system that is one of the driver safety systems for the intelligent vehicle. However, during the real driving in the daytime, driver's face is exposed to various illuminations. It makes too difficult to monitor driver's eye blinking. Therefore, we propose efficient formation of the cascaded form of Support Vector Machines (SVM) as eye verification to boost the accuracy of eye detection. Furthermore, for an efficient measurement of eye blinking, we newly define decision function that is based on the measure of eyelid movement and the weight generated by the eye classifier. In the experiments, we can show the reliable performance for our own test data acquired during a real driving in the various illumination conditions. Furthermore, through our proposed method, we use detected eye blinking for Drowsy Driver Detection System.

Original languageEnglish
Title of host publicationComputational Science - ICCS 2007 - 7th International Conference, Proceedings
PublisherSpringer Verlag
Number of pages4
EditionPART 4
ISBN (Print)9783540725893
Publication statusPublished - 2007
Event7th International Conference on Computational Science, ICCS 2007 - Beijing, China
Duration: 2007 May 272007 May 30

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 4
Volume4490 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other7th International Conference on Computational Science, ICCS 2007

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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