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Weak Classifier for Density Estimation in Eye Localization and Tracking.

Gabriel M Araujo, Felipe M L Ribeiro, Waldir S S Junior

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |April 20, 2017
    PubMed
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    This study introduces a fast weak classifier for eye detection and tracking in videos. The novel approach uses a least-squares inner product detector (IPD) with particle filters for efficient and accurate eye tracking, even with motion blur and occlusions.

    Area of Science:

    • Computer Vision
    • Machine Learning
    • Biomedical Imaging

    Background:

    • Accurate eye detection and tracking are crucial for various applications, including human-computer interaction and medical diagnostics.
    • Existing methods often struggle with real-time performance, variations in appearance, and challenging video conditions like motion blur and occlusions.

    Purpose of the Study:

    • To develop a computationally efficient and robust eye detection and tracking algorithm for video sequences.
    • To integrate a novel least-squares inner product detector (IPD) with particle filter tracking for improved performance.

    Main Methods:

    • Proposed a fast weak classifier based on a least-squares detector utilizing the inner product detector (IPD).
    • Developed two methods for integrating the IPD with a particle filter for robust tracking.

    Related Experiment Videos

  • Evaluated performance on multiple public datasets (BioID, FERET, LFPW, COFW) and custom high-definition video sequences.

    • Main Results:

    • The proposed IPD-based approach demonstrates tolerance to pattern variations and maintains good generalization.
    • The integrated IPD with particle filter tracker achieved effective eye detection and tracking in challenging video conditions, including motion blur and occlusions.
    • Quantitative evaluation on diverse datasets confirmed the algorithm's performance and efficiency.

    Conclusions:

    • The developed least-squares IPD combined with particle filtering offers an efficient and robust solution for real-time eye detection and tracking.
    • The method shows promise for applications requiring reliable eye analysis in unconstrained video environments.
    • Availability of code and data facilitates further research and development in this area.