Paper Info
Title
Improving the accuracy and reliability of remote system-calibration-free eye-gaze tracking.
Abstract
Remote eye-gaze tracking provides a means for nonintrusive tracking of the point-of-gaze (POG) of a user. For application as a user interface for the disabled, a remote system that is noncontact, reliable, and permits head motion is very desirable. The system-calibration-free pupil-corneal reflection (P-CR) vector technique for POG estimation is a popular method due to its simplicity, however, accuracy has been shown to be degraded with head displacement. Model-based POG-estimation methods were developed, which improve system accuracy during head displacement, however, these methods require complex system calibration in addition to user calibration. In this paper, the use of multiple corneal reflections and point-pattern matching allows for a scaling correction of the P-CR vector for head displacements as well as an improvement in system robustness to corneal reflection distortion, leading to improved POG-estimation accuracy. To demonstrate the improvement in performance, the enhanced multiple corneal reflection P-CR method is compared to the monocular and binocular accuracy of the traditional single corneal reflection P-CR method, and a model-based method of POG estimation for various head displacements.
Year
DOI
Venue
2009
10.1109/TBME.2009.2015955
IEEE transactions on bio-medical engineering
Keywords
Field
DocType
eye,eye-gaze,point-of-gaze estimation method,calibration,pupil-corneal reflection (p-cr),binocular accuracy,remote eye-gaze tracking,multiple corneal reflection,complex system calibration,image feature extraction,enhanced multiple corneal reflection p-cr method,monocular accuracy,user interface,single camera,system-calibration free,remote,system-calibration-free pupil-corneal reflection vector technique,head displacement,feature extraction,tracking,point-pattern matching,gesture recognition,binocular,handicapped aids,image motion analysis
Computer vision,Computer science,Gesture recognition,Robustness (computer science),Feature extraction,Eye tracking,Artificial intelligence,Monocular,User interface,Distortion,Calibration
Journal
Volume
Issue
ISSN
56
7
1558-2531
Citations 
PageRank 
References 
12
1.06
16
Authors
2
Name
Order
Citations
PageRank
Craig Hennessey114810.15
P. D. Lawrence225540.37