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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Line of Sight Estimation Accuracy Improvement using Depth Image and Ellipsoidal Model of Cornea Curvature

Author 1: Kohei Arai
Author 2: Kohya Iwamura

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2017.080568

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 5, 2017.

  • Abstract and Keywords
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Abstract: Line of sight estimation accuracy improvement is attempted using depth image (distance between user and display) and ellipsoidal model (shape of user’s eye) of cornea curvature. It is strongly required to improve line of sight estimation accuracy for perfect computer input by human eyes only. The conventional method for line of sight estimation is based on the approximation of cornea shape with ellipse function in the acquired eye image. The proposed estimation method is based on the approximation of crystalline lenses and cornea with ellipsoidal function. Therefore, much accurate approximation can be performed by the proposed method. Through experiments, it is found that depth images are useful for improvement of the line of sight estimation accuracy.

Keywords: Computer input just by sight; Computer input by human eyes only; Purkinje image; Cornea curvature

Kohei Arai and Kohya Iwamura, “Line of Sight Estimation Accuracy Improvement using Depth Image and Ellipsoidal Model of Cornea Curvature” International Journal of Advanced Computer Science and Applications(IJACSA), 8(5), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080568

@article{Arai2017,
title = {Line of Sight Estimation Accuracy Improvement using Depth Image and Ellipsoidal Model of Cornea Curvature},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080568},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080568},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {5},
author = {Kohei Arai and Kohya Iwamura}
}


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