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Neural gradient models for the measurement of image velocity

Published online by Cambridge University Press:  02 June 2009

Z. Fei Jin and
M. V. Srinivasan
Z. Fei Jin
Affiliation:
Centre for Visual Sciences, Research School of Biological Sciences, Australian National University, Canberra, A.C.T. 2601, Australia
M. V. Srinivasan
Affiliation:
Centre for Visual Sciences, Research School of Biological Sciences, Australian National University, Canberra, A.C.T. 2601, Australia
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Abstract

Although gradient schemes for detecting the motion of images and measuring their velocities are commonly used in computer vision, and although there is increasing evidence to support the existence of such schemes in biological vision, little attention has been directed to suggesting how such computations might be realized by neural hardware. This paper proposes two simple models, consisting of physiologically realistic networks of neurons, that approximate the gradient scheme. Computer simulations demonstrate that the models measure the speed of an object or pattern independently of its structural properties.

Keywords

VisionMotion perceptionImage velocityGradient modelNeural network

Information

Type
Research Article
Information
Visual Neuroscience , Volume 5 , Issue 3 , September 1990, pp. 261 - 271
Copyright
Copyright © Cambridge University Press 1990

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