REAL-TIME EYE FEATURE TRACKING FROM A VIDEO IMAGE SEQUENCE USING KALMAN FILTER

被引:40
作者
XIE, XD [1 ]
SUDHAKAR, R [1 ]
ZHUANG, HQ [1 ]
机构
[1] FLORIDA ATLANTIC UNIV, DEPT ELECT ENGN, BOCA RATON, FL 33431 USA
来源
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS | 1995年 / 25卷 / 12期
关键词
D O I
10.1109/21.478443
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Eye movement analysis is of importance in clinical studies and in research. Monitoring eye movements using video cameras has the advantage of being nonintrusive, inexpensive, and automated, The main objective of this paper is to propose an efficient approach far real-time eye feature tracking from a sequence of eye images. To this end, first we formulate a dynamic model for eye feature tracking which relates the measurements from the eye images to the tracing parameters. In our model, the center of the iris is chosen as the tracking parameter vector and the gray level centroid of the eye is chosen as the measurement vector, In our procedure for evaluating the gray level centroid, the preprocessing step such as edge detection sind curve fitting need to be performed only for the first frame of the image sequence. A discrete Kalman filter is then constructed for the recursive estimation of the eye features, while taking into account the measurement noise, Experimental results are presented to demonstrate the accuracy aspects and the real-time applicability of the proposed approach.
引用
收藏
页码:1568 / 1577
页数:10
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