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A geometric framework for nonlinear visual coding

delete2000-08-14
delete22
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OA
AI
E
Erhardt Barth *
A
Andrew B. Watson
DOI：10.1364/OE.7.000155delete
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Abstract

Abstract

En 中文
It is argued that important aspects of early and middle level visual coding may be understood as resulting from basic geometric processing of the visual input. The input is treated as a hypersurface defined by image intensity as a function of two spatial coordinates and time. Analytical results show how the Riemann curvature tensor R of this hypersurface represents speed and direction of motion. Moreover, the results can predict the selectivity of MT neurons for multiple motions and for motion in a direction along the optimal spatial orientation. Finally, a model based on integrated R components predicts global-motion percepts related to the barber-pole illusion. (C) 2000 Optical Society of America.
Keywords:
AREA MT
MOTION
MODEL
DIRECTION
MACAQUE
MECHANISMS
CURVATURE
RESPONSES
NEURONS
FILTERS

Journal

Optics Express cover
Optics Express
IF:
3.3
Papers:
6.1W
Citations:
14.3W

Organization

No organization information available