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Proceedings Paper

Real time eye tracking using Kalman extended spatio-temporal context learning
Author(s): Farzeen Munir; Fayyaz ul Amir Asfar Minhas; Abdul Jalil; Moongu Jeon
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Paper Abstract

Real time eye tracking has numerous applications in human computer interaction such as a mouse cursor control in a computer system. It is useful for persons with muscular or motion impairments. However, tracking the movement of the eye is complicated by occlusion due to blinking, head movement, screen glare, rapid eye movements, etc. In this work, we present the algorithmic and construction details of a real time eye tracking system. Our proposed system is an extension of Spatio-Temporal context learning through Kalman Filtering. Spatio-Temporal Context Learning offers state of the art accuracy in general object tracking but its performance suffers due to object occlusion. Addition of the Kalman filter allows the proposed method to model the dynamics of the motion of the eye and provide robust eye tracking in cases of occlusion. We demonstrate the effectiveness of this tracking technique by controlling the computer cursor in real time by eye movements.

Paper Details

Date Published: 19 June 2017
PDF: 5 pages
Proc. SPIE 10443, Second International Workshop on Pattern Recognition, 104431G (19 June 2017); doi: 10.1117/12.2280271
Show Author Affiliations
Farzeen Munir, Gwangju Institute of Science and Technology (Korea, Republic of)
Fayyaz ul Amir Asfar Minhas, Pakistan Institute of Engineering and Applied Sciences (Pakistan)
Abdul Jalil, International Islamic Univ. (Pakistan)
Moongu Jeon, Gwangju Institute of Science and Technology (Korea, Republic of)


Published in SPIE Proceedings Vol. 10443:
Second International Workshop on Pattern Recognition
Xudong Jiang; Masayuki Arai; Guojian Chen, Editor(s)

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