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Real Time Gaze Discrimination for Human Computer Interaction  

Park Ho sik (관동대학교 전자통신공학과 영상처리연구실)
Bae Cheol soo (관동대학교 전자통신공학과 영상처리연구실)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.30, no.3C, 2005 , pp. 125-132 More about this Journal
Abstract
This paper describes a computer vision system based on active IR illumination for real-time gaze discrimination system. Unlike most of the existing gaze discrimination techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze discrimination system can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using generalized regression neural networks (GRNNs). With GRNNs, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Futhermore, the mapping function can generalize to other individuals not used in the training. To further improve the gaze estimation accuracy, we employ a reclassification scheme that deals with the classes that tend to be misclassified. This leads to a 10% improvement in classification error. The angular gaze accuracy is about 5°horizontally and 8°vertically. The effectiveness of our gaze tracker is demonstrated by experiments that involve gaze-contingent interactive graphic display.
Keywords
Support Vector; Eye tracking; Gaze Discrimination; GRNN;
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