Novel Adaptive Eye Detection and Tracking for Challenging Lighting Conditions

  • Mahdi Rezaei
  • Reinhard Klette
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7729)

Abstract

The paper develops a novel technique that significantly improves the performance of Haar-like feature-based object detectors in terms of speed, detection rate under difficult lighting conditions, and reduced number of false-positives. The method is implemented and validated for driver monitoring under very dark, very bright, and normal conditions. The framework includes a fast adaptive detector designed to cope with rapid lighting variations, as well as an implementation of a Kalman filter for reducing the search region and indirect support of eye monitoring and tracking. The proposed methodology effectively works under low-light conditions without using infrared illumination or any other extra lighting support. Experimental results, performance evaluation, and comparing a standard Haar-like detector with the proposed adaptive eye detector, show noticeable improvements.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Mahdi Rezaei
    • 1
  • Reinhard Klette
    • 1
  1. 1.The .enpeda.. ProjectThe University of AucklandNew Zealand

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