Eye-gaze distance estimation based on gray-level intensity of image patch

This paper proposes an eye-gaze distance estimation technique based on the gray-level intensity of a single image patch from a single camera. The proposed measuring system is easy to estimate the distance between a user's eye and a computer screen. For eye gaze distance estimation, the eye gaze...

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Main Authors: Ponglangka W., Theera-Umpon N., Auephanwiriyakul S.
Format: Conference or Workshop Item
Language:English
Published: 2014
Online Access:http://www.scopus.com/inward/record.url?eid=2-s2.0-84857250710&partnerID=40&md5=a477b464015cdb5ffcd835c081dce977
http://cmuir.cmu.ac.th/handle/6653943832/1528
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Institution: Chiang Mai University
Language: English
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spelling th-cmuir.6653943832-15282014-08-29T09:29:25Z Eye-gaze distance estimation based on gray-level intensity of image patch Ponglangka W. Theera-Umpon N. Auephanwiriyakul S. This paper proposes an eye-gaze distance estimation technique based on the gray-level intensity of a single image patch from a single camera. The proposed measuring system is easy to estimate the distance between a user's eye and a computer screen. For eye gaze distance estimation, the eye gaze image is reflected by two infrared light emitting diodes attached on the vertical center of the left and right frame of a computer screen. The images are captured using a camera with a lens with focal length of 25 mm. The proposed method is tested on five users. The results are 95.64 % accuracy using linear least squares method and 96.54 % accuracy using least squares second order polynomial. The absolute errors for distance estimation are 2.97 cm and 2.47 cm using the linear least square and the least squares polynomial, respectively. The comparison shows the proposed method performs better than the pixel counts method and the two-eye distance based method. © 2011 IEEE. 2014-08-29T09:29:25Z 2014-08-29T09:29:25Z 2011 Conference Paper 9.78146E+12 10.1109/ISPACS.2011.6146205 88707 http://www.scopus.com/inward/record.url?eid=2-s2.0-84857250710&partnerID=40&md5=a477b464015cdb5ffcd835c081dce977 http://cmuir.cmu.ac.th/handle/6653943832/1528 English
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
language English
description This paper proposes an eye-gaze distance estimation technique based on the gray-level intensity of a single image patch from a single camera. The proposed measuring system is easy to estimate the distance between a user's eye and a computer screen. For eye gaze distance estimation, the eye gaze image is reflected by two infrared light emitting diodes attached on the vertical center of the left and right frame of a computer screen. The images are captured using a camera with a lens with focal length of 25 mm. The proposed method is tested on five users. The results are 95.64 % accuracy using linear least squares method and 96.54 % accuracy using least squares second order polynomial. The absolute errors for distance estimation are 2.97 cm and 2.47 cm using the linear least square and the least squares polynomial, respectively. The comparison shows the proposed method performs better than the pixel counts method and the two-eye distance based method. © 2011 IEEE.
format Conference or Workshop Item
author Ponglangka W.
Theera-Umpon N.
Auephanwiriyakul S.
spellingShingle Ponglangka W.
Theera-Umpon N.
Auephanwiriyakul S.
Eye-gaze distance estimation based on gray-level intensity of image patch
author_facet Ponglangka W.
Theera-Umpon N.
Auephanwiriyakul S.
author_sort Ponglangka W.
title Eye-gaze distance estimation based on gray-level intensity of image patch
title_short Eye-gaze distance estimation based on gray-level intensity of image patch
title_full Eye-gaze distance estimation based on gray-level intensity of image patch
title_fullStr Eye-gaze distance estimation based on gray-level intensity of image patch
title_full_unstemmed Eye-gaze distance estimation based on gray-level intensity of image patch
title_sort eye-gaze distance estimation based on gray-level intensity of image patch
publishDate 2014
url http://www.scopus.com/inward/record.url?eid=2-s2.0-84857250710&partnerID=40&md5=a477b464015cdb5ffcd835c081dce977
http://cmuir.cmu.ac.th/handle/6653943832/1528
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