Eye Tracking

Denis Leimberg, Martin Vester-Christensen

AbstractThis thesis presents a complete system for eye tracking avoiding restrictions on head movements. A learning-based deformable model - Active Appear ance Model(AAM) - is utilized for detection and tracking of the face. Several methods are proposed, described and tested for eye tracking, leading to determination of gaze.

The AAM is used for a segmentation of the eye region, as well as providing an estimate of the pose of the head.

Among several, we propose a deformable template based eye tracker, combining high speed and accuracy, independently of the resolution. We compare with a state of the art active contour approach, showing that our method is more accurate.

We conclude, that eye tracking using standard consumer cameras is feasible providing an accuracy within the measurable range.
KeywordsFace Detection, Face Tracking, Eye Tracking, Gaze Estimation, Active Appearance Models, Deformable Template, Active Contours, Particle Filtering.
TypeMaster's thesis [Academic thesis]
PublisherInformatics and Mathematical Modelling, Technical University of Denmark, DTU
AddressRichard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby
NoteSupervised by Prof. Lars Kai Hansen
Electronic version(s)[pdf]
BibTeX data [bibtex]
IMM Group(s)Intelligent Signal Processing

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