Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/54387
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dc.contributor.authorWirot Ponglangkaen_US
dc.contributor.authorNipon Theera-Umponen_US
dc.contributor.authorSansanee Auephanwiriyakulen_US
dc.date.accessioned2018-09-04T10:12:43Z-
dc.date.available2018-09-04T10:12:43Z-
dc.date.issued2015-01-01en_US
dc.identifier.issn2231525Xen_US
dc.identifier.other2-s2.0-84930791061en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84930791061&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/54387-
dc.description.abstract© 2015 by IJIR (CESER PUBLICATIONS). A novel user independent distance measurement method for eye-gaze systems based on the eigenvalues of an iris is presented in this paper. The eye-gaze images are captured using only one IP-camera with the distance between the user’s face and the screen approximately 60 to 80 centimeters. Each distance is composed of 60 predefined points on the screen and the eigenvalues of the iris from a single user is used for modeling distance estimation using the exponential, linear, logarithmic, and power regressions. The test was conducted on 30 subjects who were not a part of the training process. The experimental results substantiate the effectiveness of the exponential model which yielded 96.69% accuracy with the mean absolute error (MAE) of 2.33 centimeters. The test results obtained from linear, logarithmic, and power regressions were 95.98%, 95.33%, and 96.37% accuracy with the MAE’s of 2.78, 2.68, and 2.59 centimeters, respectively. The proposed eye-gaze distance estimation method shows high accuracy with low MAE in distance estimation compared to the pixel count and gray-level intensity approaches whose accuracy is 92.31% and 96.54%.en_US
dc.subjectComputer Scienceen_US
dc.subjectMathematicsen_US
dc.titleUsing iris region eigenvalues for user-independent eye-gaze distance estimation in single-camera setupen_US
dc.typeJournalen_US
article.title.sourcetitleInternational Journal of Imaging and Roboticsen_US
article.volume15en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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