Two-eye model-based gaze estimation from a Kinect sensor

Xiaolong Zhou*, Haibin Cai, Youfu Li, Honghai Liu

*Corresponding author for this work

    Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

    46 Citations (Scopus)

    Abstract

    In this paper, we present an effective and accurate gaze estimation method based on two-eye model of a subject with the tolerance of free head movement from a Kinect sensor. To accurately and efficiently determine the point of gaze, i) we employ two-eye model to improve the estimation accuracy; ii) we propose an improved convolution-based means of gradients method to localize the iris center in 3D space; iii) we present a new personal calibration method that only needs one calibration point. The method approximates the visual axis as a line from the iris center to the gaze point to determine the eyeball centers and the Kappa angles. The final point of gaze can be calculated by using the calibrated personal eye parameters. We experimentally evaluate the proposed gaze estimation method on eleven subjects. Experimental results demonstrate that our gaze estimation method has an average estimation accuracy around 1.99, which outperforms many leading methods in the state-of-the-art.
    Original languageEnglish
    Title of host publication2017 IEEE International Conference on Robotics and Automation (ICRA)
    PublisherIEEE
    Pages1646-1653
    ISBN (Electronic)978-1-5090-4632-4
    ISBN (Print)9781509046331
    DOIs
    Publication statusPublished - 30 May 2017
    Event2017 IEEE International Conference on Robotics and Automation, ICRA 2017 - Sands Expo and Convention Centre, Singapore
    Duration: 29 May 20173 Jun 2017
    http://www.icra2017.org/

    Publication series

    Name
    ISSN (Print)1050-4729

    Conference

    Conference2017 IEEE International Conference on Robotics and Automation, ICRA 2017
    Abbreviated titleICRA 2017
    PlaceSingapore
    Period29/05/173/06/17
    Internet address

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