Eye Gaze Location Detection Based On Iris Tracking with Web Camera

dc.contributor.authorYildiz, Metin
dc.contributor.authorYorulmaz, Muhammet
dc.contributor.researcherIDC-7863-2018en_US
dc.date.accessioned2023-08-11T12:59:07Z
dc.date.available2023-08-11T12:59:07Z
dc.date.issued2018
dc.description.abstractIn recent years, there has been an increased interest in human computer interaction systems where web cameras are used as input devices. In this study, a system developed to distinguish eye gaze locations on the screen by referring to the position of the iris part of the eye is introduced. It is aimed to distinguish more eye gaze location compared to the previous works by web cam. K-nearest neighbors classifier was used to detect eye gaze location by the feature vector of the iris center coordinates. As a result of the first experiments with 10 subjects, the 17 different eye gaze locations on the screen have classified with an average of 97.64% accuracy. It has been observed that only the two adjacent points near the center of the screen in the vertical direction are detected incorrectly. It is expected to increase the classification performance ratio by not using these two incorrectly detected points in future studies.en_US
dc.identifier.issn2165-0608en_US
dc.identifier.scopus2-s2.0-85050824130en_US
dc.identifier.urihttp://hdl.handle.net/11727/10251
dc.identifier.wos000511448500167en_US
dc.language.isoturen_US
dc.relation.journal26th IEEE Signal Processing and Communications Applications Conference (SIU)en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectHuman computer interactionen_US
dc.subjectimage processingen_US
dc.subjecteye gaze detectionen_US
dc.subjectK-nearest neighbors classifieren_US
dc.titleEye Gaze Location Detection Based On Iris Tracking with Web Cameraen_US
dc.typeconferenceObjecten_US

Files

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: