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Related Experiment Video

Updated: May 24, 2026

Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition
07:45

Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition

Published on: July 21, 2020

A New Biased Discriminant Analysis Using Composite Vectors for Eye Detection.

Chunghoon Kim, Sang-Il Choi, M Turk

    IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
    |March 14, 2012
    PubMed
    Summary

    This study introduces composite biased discriminant analysis (C-BDA) for real-time eye detection. The novel C-BDA method achieves high accuracy and robustness across various conditions, demonstrating its potential for facial recognition applications.

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    Area of Science:

    • Computer Vision
    • Machine Learning
    • Biometrics

    Background:

    • Accurate eye detection is crucial for facial recognition and analysis.
    • Existing methods face challenges with variations in pose, illumination, and occlusion.

    Purpose of the Study:

    • To develop a novel and robust eye detection method using composite biased discriminant analysis (C-BDA).
    • To evaluate the performance and real-time capabilities of the proposed eye detector.

    Main Methods:

    • Proposed a new biased discriminant analysis (BDA) using composite vectors, termed C-BDA.
    • Constructed a hybrid cascade detector combining Haar-like features and C-BDA composite features.
    • Achieved real-time execution with an average time of 5.5 ms on a typical PC.

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    Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
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    Functional Magnetic Resonance Imaging (fMRI) of the Visual Cortex with Wide-View Retinotopic Stimulation
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    Functional Magnetic Resonance Imaging (fMRI) of the Visual Cortex with Wide-View Retinotopic Stimulation

    Published on: December 8, 2023

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    Last Updated: May 24, 2026

    Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition
    07:45

    Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition

    Published on: July 21, 2020

    Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
    08:25

    Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

    Published on: May 7, 2019

    Functional Magnetic Resonance Imaging (fMRI) of the Visual Cortex with Wide-View Retinotopic Stimulation
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    Main Results:

    • Achieved high detection rates: 98.0% on the CMU PIE database and 95.1% on a real-world dataset.
    • Demonstrated robust performance against variations in facial pose, illumination, eyeglasses, and partial occlusion.
    • Eye coordinates from the detector yielded face recognition performance comparable to manually located coordinates.

    Conclusions:

    • The proposed C-BDA method offers a robust and efficient solution for real-time eye detection.
    • The detector's accuracy is comparable to ground-truth data, making it suitable for biometric applications.
    • The method shows significant potential for improving face recognition systems.