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dc.contributor.authorNatalina De Fatima Gusmao-
dc.contributor.authorPark, J.-M.-
dc.contributor.authorOh, S.-R.-
dc.date.accessioned2024-01-20T05:03:03Z-
dc.date.available2024-01-20T05:03:03Z-
dc.date.created2021-09-02-
dc.date.issued2016-02-
dc.identifier.issn1343-4500-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/124487-
dc.description.abstractExisting eye tracking schemes typically require invasive or expensive hardware in order to get the accurate results. This paper describes a non-invasive remote eye tracking method that only requires a webcam. In this work we employed several methods that are consisted of three processes, such as face detection, eye detection, and pupil tracking. For face and eye detection, we used Haar feature-based cascade classifier. For pupil tracking, we modified a method so-called means of gradients by implementing preprocessing and post-processing techniques. Finally, we integrated these methods for eye tracking. The experimental results demonstrate that the proposed scheme using a built-in webcam does support eye tracking under various human conditions such as: low contrast, dominant eyelids/eyelashes, any types of skin colors, and reflection of glasses; and environmental situations such as indoor and outdoor. ? 2016 International Information Institute.-
dc.languageEnglish-
dc.publisherInternational Information Institute-
dc.titleSimple and robust eye tracking with a webcam-
dc.typeArticle-
dc.description.journalClass1-
dc.identifier.bibliographicCitationInformation, v.19, no.2, pp.577 - 586-
dc.citation.titleInformation-
dc.citation.volume19-
dc.citation.number2-
dc.citation.startPage577-
dc.citation.endPage586-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.identifier.scopusid2-s2.0-84962580384-
dc.type.docTypeArticle-
dc.subject.keywordAuthorComputer vision-
dc.subject.keywordAuthorEye tracking-
dc.subject.keywordAuthorFeature detection-
dc.subject.keywordAuthorPupil tracking-
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KIST Article > 2016
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