The following technical report on visual segmentation is available
from MIT AI Publication, via
ftp://publications.ai.mit.edu/ai-publications/1500-1999/AIM-1640.ps
TITLE:
Pre-attentive segmentation in the primary visual cortex
AUTHOR:
Zhaoping Li
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, in a new framework called Segmentation Without Classification.
This means that segmentation of an image into regions occurs without
classification of features within a region or comparison of features between
regions. This segmentation framework is simpler than previous computational
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 tricky in conventional
methods. The cortex 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. 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. This proposal is implemented in a biologically based model of
V1, and demonstrated using examples of texture segmentation and
figure-ground segregation. The model performs segmentation in exactly
the same neural circuit that solves the dual problem of the enhancement
of contours, as is suggested by experimental observations. Its behavior
is compared with psychophysical and physiological data on segmentation,
contour enhancement, and contextual influences. We discuss the implications
of Segmentation Without Classification and the predictions of our
V1 model, and relate it to other phenomena such as asymmetry in visual search.
Sincerely,
Zhaoping.
PS: sorry if you have already received this announcement from connectionists.