Non-rigid eye movement tracking and eye state quantification

Masrullizam Mat Ibrahim, John Soraghan, Lykourgos Petropoulakis

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

4 Citations (Scopus)

Abstract

Tracking and quantifying the eye's state in real-time whilst also accounting for object size variation is crucial in computer vision systems for Human Computer Interaction (HCI) applications and fatigue detection techniques. This paper presents a novel approach to track and quantify the eye states using the Mean Shift tracking algorithm enhanced by an adaptive scale. The iris is used as a target model for Mean Shift tracking and the moment features are used to estimate the iris area in order to quantify the state of the eye. The proposed approach to tracking non-rigid eye movement and to providing eye state quantification is shown to produce very accurate results.
Original languageEnglish
Title of host publication2012 19th International Conference on Systems, Signals and Image Processing (IWSSIP)
PublisherIEEE
Pages280-283
Number of pages4
ISBN (Print)9781457721915
Publication statusPublished - 11 Apr 2012

Keywords

  • fatigue detection techniques
  • eye movement tracking
  • eye state quantification
  • mean shift tracking
  • adaptive scale

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  • Cite this

    Mat Ibrahim, M., Soraghan, J., & Petropoulakis, L. (2012). Non-rigid eye movement tracking and eye state quantification. In 2012 19th International Conference on Systems, Signals and Image Processing (IWSSIP) (pp. 280-283). IEEE.