Visual Segmentation by Contextual
Influences via Intra-Cortical Interactions in the Primary Visual Cortex
Zhaoping Li
Gatsby Computational Neuroscience Unit
University College London
Network: Computation in Neural Systems Volumn 10, Number 2, May
1999. Page 187-212
Abstract
Stimuli outside classical receptive fields have been shown to exert
significant influence over the activities of neurons in primary visual cortex. We propose
that contextual influences are used for pre-attentive visual segmentation. The difference
between contextual influences near and far from region boundaries makes neural activities
near region boundaries higher than elsewhere, making boundaries more salient for
perceptual pop-out. The cortex thus computes global region boundaries by detecting the
breakdown of homogeneity or translation invariance in the input, using local
intra-cortical interactions mediated by the horizontal connections. This proposal is
implemented in a biologically based model of V1, and demonstrated using examples of
texture segmentation and figure-ground segregation. The model is also the first that
performs texture or region segmentation in exactly the same neural circuit that solves the
dual problem of the enhancement of contours, as is suggested by experimental observations.
The computational framework in this model is simpler than previous approaches, making it
implementable by V1 mechanisms, though higher level visual mechanisms are needed to refine
its output. However, it easily handles a class of segmentation problems that are known to
be tricky. Its behavior is compared with psychophysical and physiological data on
segmentation, contour enhancement, contextual influences, and other phenomena such as
asymmetry in visual search.
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