REMINDER: BISC Seminar Today Features Prof. Stark of EECS/ME

Lotfi Zadeh (zadeh@eecs.berkeley.edu)
Mon, 28 Apr 1997 12:50:21 +0200


Top-Down Vision in Humans and Robots

BISC Seminar

Professor Lawrence W. Stark
EECS and ME Departments
University of California at Berkeley
stark@blur.berkeley.edu

24 April 1997
310 Soda Hall
4:00-5:00pm

Abstract:

The scanpath theory suggests that a top-down internal cognitive model of
what we "see" controls not only our vision, but also drive the sequences of
rapid eye movements and fixations, or glances, that so efficiently travel
over a scene or picture of interest. The contrary belief is that features of
the external world control eye fixations and vision in a bottom-up mode by
impinging on the retina and sending signals to the brain.

Philosophers have speculated that we "see in our mind's eye", but until the
scanpath theory, little evidence supported this conjecture. Eye movements
are an essential part of vision because of the dual nature of the visual
system -- i) the fovea, a narrow field, about 1/2 to 2 degrees, of high
resolution vision; and ii) the periphery, a very wide field, about 180
degrees, of low resolution vision, sensitive to motion and flicker. Eye
movements must carry the fovea to each part of a scene or picture or page of
reading matter to be processed with high resolution. An illusion of clarity
exists, that we 'see' the entire visual field with high resolution, but this
cannot be true.

The cognitive model of what we expect to see is what we actually 'see'. This
internal model drives our eye movements in a "scanpath", a repetitive,
sequential set of saccades and fixations over subfeatures of the picture or
scene, so as to check out and confirm the model. These scanpath sequences
are idiosyncratic to the subject and to the picture. Experiments have shown
that when we look at ambiguous pictures patterns of eye movement change with
the mental image we have of the ambiguous figure. When we engage in visual
imagery, looking at a blank screen and visualizing a previously seen figure,
our scanpath eye movements are similar whether viewing the figure or the
blank screen. This provides strong evidence that the internal cognitive
model and not the external world (since this is absent in visual imagery)
drives the scanpath. Recent evidence uses string editing distances to
quantitate the similarity and dissimilarity between scanpaths. Also, studies
of visual search indicates that a primitive form of pre-cognitive spatial
model controls a 'searchpath' sequence of eye movements.

Buttressed by these new views of top-down human vision, we have applied the
scanpath theory to robotic vision. Here we use our knowledge of the spatial
layout of the robotic working environment, including position and
orientation of the video cameras, and the nature of the robots and the
work-pieces to develop a "cognitive model". This computer model then
controls the image processing. Regions of interest, ROIs, are generated so
that image processing, such as local thresholding and centroid calculations,
can be carried out efficiently and robustly. Only those subfeatures
essential for identification and control are processed, reducing the
computational task greatly. The model not only controls image processing, as
in human vision in the scanpath mode, but can also control the robots, the
cameras, and displays for the supervisory human teleoperators. The model
also serves to reduce communication bandwidth requirements since only
commanded and correction model parameters are transmitted. Thus a top-down
visual scheme satisfies a visual feedback control system for robots.

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