Eye Tracking Using Artificial Neural Networks for Human Computer Interaction

This paper describes an ongoing project that has the aim to develop a low cost application to replace a computer mouse for people with physical impairment. The application is based on an eye tracking algorithm and assumes that the camera and the head position are fixed. Color tracking and template m...

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Bibliographic Details
Published in:Physiological research Vol. 60; no. 5; pp. 841 - 844
Main Authors: DEMJÉN, E., ABOŠI, V., TOMORI, Z.
Format: Journal Article
Language:English
Published: Czech Republic Institute of Physiology 01.01.2011
Subjects:
Accuracy
Algorithms
Cameras
Eye Movements - physiology
Female
Humans
Image Interpretation, Computer-Assisted - methods
Male
Methods
Neural networks
Neural Networks, Computer
Pattern Recognition, Automated - methods
Photography - methods
Retina - anatomy & histology
Retina - physiology
Retinoscopy - methods
Sensitivity and Specificity
Studies
User-Computer Interface
Young Adult
ISSN:0862-8408, 1802-9973, 1802-9973
Online Access:Get full text
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Summary:This paper describes an ongoing project that has the aim to develop a low cost application to replace a computer mouse for people with physical impairment. The application is based on an eye tracking algorithm and assumes that the camera and the head position are fixed. Color tracking and template matching methods are used for pupil detection. Calibration is provided by neural networks as well as by parametric interpolation methods. Neural networks use back-propagation for learning and bipolar sigmoid function is chosen as the activation function. The user’s eye is scanned with a simple web camera with backlight compensation which is attached to a head fixation device. Neural networks significantly outperform parametric interpolation techniques: 1) the calibration procedure is faster as they require less calibration marks and 2) cursor control is more precise. The system in its current stage of development is able to distinguish regions at least on the level of desktop icons. The main limitation of the proposed method is the lack of head-pose invariance and its relative sensitivity to illumination (especially to incidental pupil reflections).
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ISSN:0862-8408
1802-9973
1802-9973
DOI:10.33549/physiolres.932117