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An Active Vision Architecture based on Iconic Representations |
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@TechReport{Rao:TR95,
author = {Rajesh P.N. Rao and Dana H. Ballard},
title = {An Active Vision Architecture based on Iconic Representations},
institution = {Comp Sci Dept University of Rochester},
year = {1995},
number = {548},
address = {Rochester NY},
month = {March},
abstract = {
Active vision systems have the capability of continuously interacting with the
environment. The rapidly changing environment of such systems means that it is
attractive to replace static representations with visual routines that compute
information on demand. Such routines place a premium on image data structures that
are easily computed and used.
The purpose of this paper is to propose a general active vision architecture based
on efficiently computable iconic representations. This architecture employs two
primary visual routines, one for identifying the visual image near the fovea (object
identification), and another for locating a stored prototype on the retina (object
localization). This design allows complex visual behaviors to be obtained by
composing these two routines with different parameters.
The iconic representations are comprised of high-dimensional feature vectors
obtained from the responses of an ensemble of Gaussian derivative spatial filters
at a number of orientations and scales. These representations are stored in two
separate memories. One memory is indexed by image coordinates while the other is
indexed by object coordinates. Object localization matches a localized set of model
features with image features at all possible retinal locations. Object
identification matches a foveal set of image features with all possible model
features. We present experimental results for a near real-time implementation of
these routines on a pipeline image processor and suggest relatively simple
strategies for tackling the problems of occlusions and scale variations. We also
discuss two additional visual routines one for top-down foveal targeting using
log-polar sensors and another for looming detection, which are facilitated by the
proposed architecture. }
}