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

9 Citations (Scopus)

Abstract

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
Pages546-549
Number of pages4
EditionPART 4
Publication statusPublished - 2007 Dec 1
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

Other

Other7th International Conference on Computational Science, ICCS 2007
CountryChina
CityBeijing
Period07/5/2707/5/30

Fingerprint

Intelligent Vehicle
Intelligent vehicle highway systems
Driver
Lighting
Security systems
Support vector machines
Classifiers
Illumination
Experiments
Support Vector Machine
Monitor
Safety
Classifier
Face
Experiment

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Park, I., Ahn, J. H., & Byun, H. (2007). Efficient measurement of the eye blinking by using decision function for intelligent vehicles. In Computational Science - ICCS 2007 - 7th International Conference, Proceedings (PART 4 ed., pp. 546-549). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4490 LNCS, No. PART 4).
Park, Ilkwon ; Ahn, Jung Ho ; Byun, Hyeran. / Efficient measurement of the eye blinking by using decision function for intelligent vehicles. Computational Science - ICCS 2007 - 7th International Conference, Proceedings. PART 4. ed. 2007. pp. 546-549 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 4).
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abstract = "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.",
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Park, I, Ahn, JH & Byun, H 2007, Efficient measurement of the eye blinking by using decision function for intelligent vehicles. in Computational Science - ICCS 2007 - 7th International Conference, Proceedings. PART 4 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 4, vol. 4490 LNCS, pp. 546-549, 7th International Conference on Computational Science, ICCS 2007, Beijing, China, 07/5/27.

Efficient measurement of the eye blinking by using decision function for intelligent vehicles. / Park, Ilkwon; Ahn, Jung Ho; Byun, Hyeran.

Computational Science - ICCS 2007 - 7th International Conference, Proceedings. PART 4. ed. 2007. p. 546-549 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4490 LNCS, No. PART 4).

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

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Park I, Ahn JH, Byun H. Efficient measurement of the eye blinking by using decision function for intelligent vehicles. In Computational Science - ICCS 2007 - 7th International Conference, Proceedings. PART 4 ed. 2007. p. 546-549. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 4).