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2D Linear oculomotor plant mathematical model: Verification and biometric applications

2D Linear oculomotor plant mathematical model: Verification and biometric applications 2D Linear Oculomotor Plant Mathematical Model: Verification and Biometric Applications OLEG KOMOGORTSEV, COREY HOLLAND, SAMPATH JAYARATHNA, and ALEX KARPOV, Texas State University This article assesses the ability of a two-dimensional (2D) linear homeomorphic oculomotor plant mathematical model to simulate normal human saccades on a 2D plane. The proposed model is driven by a simplified pulse-step neuronal control signal and makes use of linear simplifications to account for the unique characteristics of the eye globe and the extraocular muscles responsible for horizontal and vertical eye movement. The linear nature of the model sacrifices some anatomical accuracy for computational speed and analytic tractability, and may be implemented as two one-dimensional models for parallel signal simulation. Practical applications of the model might include improved noise reduction and signal recovery facilities for eye tracking systems, additional metrics from which to determine user effort during usability testing, and enhanced security in biometric identification systems. The results indicate that the model is capable of produce oblique saccades with properties resembling those of normal human saccades and is capable of deriving muscle constants that are viable as biometric indicators. Therefore, we conclude that sacrifice in the anatomical accuracy of the model produces negligible effects on http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Applied Perception (TAP) Association for Computing Machinery

2D Linear oculomotor plant mathematical model: Verification and biometric applications

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References (62)

Publisher
Association for Computing Machinery
Copyright
Copyright © 2013 by ACM Inc.
ISSN
1544-3558
DOI
10.1145/2536764.2536774
Publisher site
See Article on Publisher Site

Abstract

2D Linear Oculomotor Plant Mathematical Model: Verification and Biometric Applications OLEG KOMOGORTSEV, COREY HOLLAND, SAMPATH JAYARATHNA, and ALEX KARPOV, Texas State University This article assesses the ability of a two-dimensional (2D) linear homeomorphic oculomotor plant mathematical model to simulate normal human saccades on a 2D plane. The proposed model is driven by a simplified pulse-step neuronal control signal and makes use of linear simplifications to account for the unique characteristics of the eye globe and the extraocular muscles responsible for horizontal and vertical eye movement. The linear nature of the model sacrifices some anatomical accuracy for computational speed and analytic tractability, and may be implemented as two one-dimensional models for parallel signal simulation. Practical applications of the model might include improved noise reduction and signal recovery facilities for eye tracking systems, additional metrics from which to determine user effort during usability testing, and enhanced security in biometric identification systems. The results indicate that the model is capable of produce oblique saccades with properties resembling those of normal human saccades and is capable of deriving muscle constants that are viable as biometric indicators. Therefore, we conclude that sacrifice in the anatomical accuracy of the model produces negligible effects on

Journal

ACM Transactions on Applied Perception (TAP) – Association for Computing Machinery

Published: Oct 1, 2013

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