ADVANCES IN VISION-BASED DETECTION OF DRIVER FATIGUE

This paper describes advances towards a non-intrusive approach for real-time detection of driver fatigue. It uses a color video camera that points directly towards the driver's face. It monitors the driver's eyes in order to detect micro-sleeps (short periods of sleep of about 3-4 seconds). The system deals with skin color information in order to search for the face in the input space. Allowing only those pixels with skin like color to be present, we perform blob operation in order to determine the exact position of the face. We reduce the search space by analyzing the horizontal gradient map of the face taking into account the knowledge that eye regions in the face have a great change in the horizontal intensity gradient. In order to find the exact location of the pupil, we use gray scale model matching. Using this pattern recognition technique, we track the eyes in the video frame sequence until we detect errors in the tracking module. We also use the same pattern recognition technique to determine whether the eye is open or closed. If the eyes remain closed for an abnormally long period (3-4 sec), the system draws the conclusion that the person is falling asleep and issues some kind of warning signal. The system uses a Pentium Pro 200 MHz personal computer with a Matrox Genesis imaging board, which holds a Texas Instruments TMS320C80 DSP chip. The systems performance is 15 frames per second for tracking and 10 frames per second for fatigue detection.

  • Supplemental Notes:
    • Publication Date: 1999 Published By: ITS America, Washington DC
  • Corporate Authors:

    University of Minnesota, Minneapolis

    Artificial Intelligence, Robotics, and Vision Lab
    Minneapolis, MN  United States  55455-0220
  • Authors:
    • Singh, Sarbjit
    • Papanikolopoulos, Nikolaos P
  • Conference:
  • Publication Date: 1999

Language

  • English

Media Info

  • Pagination: 13 p.

Subject/Index Terms

Filing Info

  • Accession Number: 00778050
  • Record Type: Publication
  • Source Agency: UC Berkeley Transportation Library
  • Files: PATH
  • Created Date: Nov 17 1999 12:00AM