Eye tracking using markov models

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buir.contributor.authorÇetin, A. Enis
buir.contributor.orcidÇetin, A. Enis|0000-0002-3449-1958
dc.citation.epage821en_US
dc.citation.spage818en_US
dc.citation.volumeNumber3en_US
dc.contributor.authorBağcı, A. M.en_US
dc.contributor.authorAnsari, R.en_US
dc.contributor.authorKhokhar, A.en_US
dc.contributor.authorÇetin, A. Enisen_US
dc.coverage.spatialCambridge, England, UKen_US
dc.date.accessioned2016-02-08T11:52:26Z
dc.date.available2016-02-08T11:52:26Z
dc.date.issued2004en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 23-26 August 2004en_US
dc.descriptionConference Name: 17th International Conference on Pattern Recognition, IEEE 2004en_US
dc.description.abstractWe propose an eye detection and tracking method based on color and geometrical features of the human face using a monocular camera. In this method a decision is made on whether the eyes are closed or not and, using a Markov chain framework to model temporal evolution, the subject's gaze is determined. The method can successfully track facial features even while the head assumes various poses, so long as the nostrils are visible to the camera. We compare our method with recently proposed techniques and results show that it provides more accurate tracking and robustness to variations in view of the face. A procedure for detecting tracking errors is employed to recover the loss of feature points in case of occlusion or very fast head movement. The method may be used in monitoring a driver's alertness and detecting drowsiness, and also in applications requiring non-contact human computer interaction.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T11:52:26Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2004en
dc.identifier.doi10.1109/ICPR.2004.1334654en_US
dc.identifier.issn1051-4651en_US
dc.identifier.urihttp://hdl.handle.net/11693/27401
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/ICPR.2004.1334654en_US
dc.source.titleProceedings of the 17th International Conference on Pattern Recognition, IEEE 2004en_US
dc.subjectError trackingen_US
dc.subjectEye trackingen_US
dc.subjectGeometrical featuresen_US
dc.subjectModel temporal evolutionen_US
dc.subjectColoren_US
dc.subjectError detectionen_US
dc.subjectFeature extractionen_US
dc.subjectHuman computer interactionen_US
dc.subjectMarkov processesen_US
dc.subjectMathematical modelsen_US
dc.subjectPrincipal component analysisen_US
dc.subjectRobustness (control systems)en_US
dc.subjectObject recognitionen_US
dc.titleEye tracking using markov modelsen_US
dc.typeConference Paperen_US

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