Sleep Technology for Driving Safety

Sei-Wang Chen, Kuo Peng Yao, Hui Wen Lin

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

In this chapter, a vision system for monitoring driver vigilance is presented. The level of vigilance is determined by integrating a number of facial parametric values including: percentage of eye closure over time, average eye closure duration, eye blinking frequency, average degree of gaze, average duration of mouth openness and head nodding frequency. Initially, facial features including the eyes, mouth and head are first located in the input video sequence. They are then tracked over subsequent images. Facial parameters are estimated during facial feature tracking. A number of video sequences having drivers of both sex and of different ages under various illuminations and road conditions are employed to test the performance of the proposed system. Finally, we suggest future work on how to extend the system in terms of both efficiency and effectiveness.

Original languageEnglish
Title of host publicationIntelligent Systems, Control and Automation
Subtitle of host publicationScience and Engineering
PublisherSpringer Netherlands
Pages219-243
Number of pages25
DOIs
Publication statusPublished - 2012 Jan 1

Publication series

NameIntelligent Systems, Control and Automation: Science and Engineering
Volume64
ISSN (Print)2213-8986
ISSN (Electronic)2213-8994

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Keywords

  • Driver vigilance monitoring system
  • Facial feature detection and tracking
  • Facial parameter estimation
  • Fuzzy reasoning
  • Vision system

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Mechanical Engineering
  • Computer Science Applications
  • Control and Optimization

Cite this

Chen, S-W., Yao, K. P., & Lin, H. W. (2012). Sleep Technology for Driving Safety. In Intelligent Systems, Control and Automation: Science and Engineering (pp. 219-243). (Intelligent Systems, Control and Automation: Science and Engineering; Vol. 64). Springer Netherlands. https://doi.org/10.1007/978-94-007-5470-6_12