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Deterministic and Stochastic Methods for Gaze Tracking in Real-Time

  • Javier Orozco
  • F. Xavier Roca
  • Jordi Gonzàlez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4673)

Abstract

Psychological evidence demonstrates how eye gaze analysis is requested for human computer interaction endowed with emotion recognition capabilities. The existing proposals analyse eyelid and iris motion by using colour information and edge detectors, but eye movements are quite fast and difficult for precise and robust tracking. Instead, we propose to reduce the dimensionality of the image-data by using multi-Gaussian modelling and transition estimations by applying partial differences. The tracking system can handle illumination changes, low-image resolution and occlusions while estimating eyelid and iris movements as continuous variables. Therefore, this is an accurate and robust tracking system for eyelids and irises in 3D for standard image quality.

Keywords

Appearance Model Warping Function Gaussian Parameter Tracking Vector Eyelid Position 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Javier Orozco
    • 1
  • F. Xavier Roca
    • 1
  • Jordi Gonzàlez
    • 2
  1. 1.Computer Vision Center & Dept. de Ciències de la Computació, Edifici O, Campus UAB, 08193 BellaterraSpain
  2. 2.Institut de Robòtica i Informàtica Industrial (UPC – CSIC), C. Llorens i Artigas 4-6, 08028, BarcelonaSpain

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