Transcript Macquarie University July 25, 2002 Vision needs non-conceptual connections to objects in the world (just as concepts do)  Introduction to a theory of visual indexes.

Macquarie University
July 25, 2002
Vision needs non-conceptual
connections to objects in the
world (just as concepts do)
 Introduction to a theory of
visual indexes (aka FINSTs)
Zenon Pylyshyn
Rutgers Center for Cognitive Science
Plan of talk: Visual Indexes
Theoretical motivations behind the FINST theory
 The need for a primitive mechanism of individuation
 Because individuation must be of distal objects, we
have the Correspondence Problem: When do two
proximal tokens correspond to the same distal object?
• A special case: incremental construction of visual representations
Empirical studies of individuation and indexing
 Object-specific effects (static & moving objects)
 Multiple Object Tracking technique.
What, if any, encoded properties are used to
individuate, index, and track objects?
Visual Indexes (FINSTs) and what they
mean for vision science and cognitive science
The need for a mechanism
that individuates objects
Examples of solving the
correspondence problem
Individuating distal objects
requires solving the
correspondence problem
Object-based allocation of
visual attention
A special case of the correspondence problem occurs
when visual representations
are constructed over time.
Multiple Object Tracking
and Visual Indexes: what it
means for connecting
vision and the world
An important function of early vision is
to individuate and select token elements
(let’s call them “objects” for now)
 The most basic perceptual operation is the
individuation and selection that precedes the
formulation of perceptual judgments.
 Making visual judgments presupposes that
the things (objects) that judgments are about
have been individuated and selected (or
indexed – i.e., made accessible).
Another way to put this is that the arguments
of perceptual predicates P(x,y,z,…) must be
bound to things in the world in order for the
judgment to have perceptual content.
Several objects must be picked out
at once in relational judgments
 For example, when we judge that certain objects are
collinear, we must select (and the visual system must
be able to refer to) the relevant individual objects.
Several objects must be picked out
at once in relational judgments
 The same is true for other relational predicates,
like inside or on-the-same-contour… etc. We
must pick out the relevant individual objects first.
How do we select (and index)
objects in our field of view?
 The principal way we select individual objects is
by foveating them – by looking directly at them
(Notice that this results in a deictic reference).
 We can also select with focal attention, which is
independent of direction of gaze.
 Focal attention appears to be unitary, yet we can
select more than one thing at a time (e.g., in
making a relational judgment). So it seems that
we need to distinguish attending from selecting:
That’s where Visual Indexes or FINSTs come in.
 A question for later: In virtue of what properties
are primitive objects individuated and indexed?
Indexes must individuate and select objects
in the world. This leads to the ubiquitous
correspondence problem in vision
 Apparent motion, stereo vision, tracking, and
very many visual computations face the problem
of identifying which proximal image-features
correspond to the same individual distal object.
 Less well known is the correspondence problem
faced when a single visual representation is
constructed incrementally over time.
 The way the correspondence problem is solved
determines what the vision system counts as an
individual. These primitive individuals (called
“objects”) are thus mind-dependent.
Example of the correspondence
problem for apparent motion
The gray disks correspond to the first flash and the black ones
to the second flash. Which of the 24 possible matches will the
visual system select as the solution to this correspondence
problem? What principal does it use? (Dawson & Pylyshyn, 1988)
Curved matches
Linear matches
One of the most troubling forms of
the correspondence problem occurs
because visual representations are
constructed incrementally over time
It is clear that when vision requires eye
movements, a visual representation is constructed
incrementally. But there is also evidence that
percepts are built up over time even for the
automatic perception of simple forms. So this
type of correspondence problem is routine in
vision. Why does it constitute a special problem?
Example: Drawing a diagram and noticing its properties
Some of the distinct “views” while exploring the diagram
The correspondence problem for
incremental construction of a visual
representation
 When a property F of some particular individual
(token) object O is noticed or encoded, the visual
system must check whether object O is already
represented. If it is, the new property must be
associated with the existing representation of O.
 If the only way to identify a particular individual
object O is by its description, then the way to solve
this correspondence problem is to find an object in
memory that bears a particular description (one that
had been unique at the time). Which description? If
objects can change their properties, we don’t know
under what description the object was last stored.
Perhaps we look for an object with a description that
overlaps the present one, or perhaps we construct a
description that somehow incorporates time.
The correspondence problem for
incremental construction of a visual
representation
 Even if it were otherwise feasible to solve the
correspondence problem by searching for a
unique past description, this would in general be
computationally intractable (technically, matching
descriptions is an NP-hard problem).
In any case it is unlikely that this is what our
visual system does, for many reasons – e.g., we do
not in general find it more difficult to construct a
representation of a scene that has many identical
parts, as would be predicted from this technique
(since it would then be more difficult to find a
unique descriptor for each object and the
correspondence problem would quickly grow in
complexity).
In virtue of what visual properties
are objects individuated?
The most plausible property used in selecting
and accessing an object is its location (this is
often the only unique property available).
The notion of a pointer suggests the use of
location-as-access.
Virtually all theories of visual attention and
property detection assume that we access an
object’s properties by first retrieving its
location.
But….
 Although there is a great deal of evidence for the
priority of encoding location, this does not show
that properties must be accessed by their location.
 In studies in which objects remain stationary,
location is confounded with individuality since in
these cases being at a particular location is
coextensive with being a particular individual.
 But there is also recent evidence that we can
access an object’s properties solely by virtue of
the object’s persistence qua individual. This is
referred to as object-based attention.
Unconfounding location and
individuality
There are at least two possible ways to
unconfound location and individuality:
1. use moving objects
2. use objects whose identity and/or
‘motion’ is independent of their spatial
location.
Distinguishing access-by-location
and access-by-individual
1. Moving objects
 Object-specific priming (Object Files)
 Object-specific Inhibition of Return *
 Simultanagnosia & Visual Neglect *
 Multiple Object Tracking (MOT)
2. Spatially coincident objects
 Single-object advantage *
 tracking in “feature space”
* Some of these may be omitted for lack of time
Moving object studies…
Object-specific Priming
(aka object-file theory: Kahneman et al. 1992)
Sequence of displays in a simple Object-Priming experiment
Moving object studies…
Inhibition of Return
(Tipper et al. 1991)
Moving object studies…
“Inhibition of Return” moves
with the object that is inhibited
Multiple Object Tracking Experiments
How do we do it? What properties of individual objects do we use?
People can track 5 or more objects
under a wide variety of conditions
Objects don’t even have to avoid collisions!
Objects can even disappear from view,
as long as they do it in the right way
There must be local evidence of an occluding surface.
A possible location-updating tracking algorithm
1. While the targets are visually distinct, scan attention to each target
2.
3.
4.
5.
6.
7.
and encode its location on a list. When targets begin to move;
For n=1 to 4; Check the n’th position in the list and retrieve the
location Loc(n) listed there.
Go to location Loc(n). Find the closest element to Loc(n).
Update the n’th position on the list with the actual location of the
element found in #3. This becomes the new value of Loc(n).
Move attention to the location encoded in the next list position,
Loc(n+1).
Repeat from #2 until elements stop moving.
Go to each Loc(n) in turn and report elements located there.
We compared the above algorithm with human performance on the very
same displays. We assume (1) focal attention is required to encode
locations (i.e., encoding is not parallel), (2) focal attention is unitary
and has to be scanned from location to location. But it assumes no
encoding (or dwell) time at each element.
Predicted performance of the location updating
algorithm as a function of attention scanning speed
What properties are used in
(a) selecting objects, and
(b) tracking objects?
 Notice that these are different
operations and need not involve
the same properties
Role of object properties
What properties can be used to
select (index) an object in MOT?
We have evidence that under certain
conditions selecting objects can be done
either automatically or voluntarily.
 Automatic selection requires “popout” features
(sudden appearance, motion, stereo depth, etc)
 Voluntary selection can use any discriminable
property, but the objects must be attended
serially and the property must be available
long enough for this to occur (Annan study)
Role of object properties (continued)
What properties can be used to
track indexed objects?
 We have some evidence that observers do not
encode or use intrinsic object properties (e.g.,
color, shape) during tracking:
 When we stop and ask, observers cannot tell us what
properties objects had and they do not notice when
properties like color/shape change during occlusion;
 There is some evidence that tracking occurs (at least
for small numbers of objects) even if it is not taskrelevant (e.g., object-based priming and IOR);
 We have some evidence that when objects differ in
non-identifying (asynchronously changing) properties,
they are not tracked any better than if they do not
differ in these properties.
Role of object properties (continued)
Do observers use some version
of object locations for tracking?
Perhaps instead of using the location-
updating method to track, observers respond
to the objects’ “spatiotemporal trjectory”
property (e.g., to their “space-time worms”).
Spatiotemporal continuity as a
property that is used in tracking
Could a mechanism could respond to
spatiotemporal continuity without
responding to object identity?
The notion of spatiotemporal trajectory
presupposes that it is the trajectory of a single
individual object, and not a sequence of timeslices of different objects. Therefore it
assumes that the individual object has been
selected and tracked. Responding to a
spatiotemporal trajectory may be the same as
tracking an object’s identity.
A note about responding to trajectories
as opposed to responding individuals
 If we think of tracking as the establishment of a
correspondence between objects at time t = i and
time t = i+1, then this constitutes a graph with
objects as nodes and trajectories as edges.
 For every graph there is a dual in which nodes and
edges are interchanged.
 Therefore, responding to objects is mathematically
equivalent to responding to trajectories.
 But these may still be empirically distinguishable,
just as different instantiations of Euclidean axioms
are empirically distinguishable.
Another way to unconfound
individuality and location
Can we attend to objects that are not
distinguished by their location?
 Single-object advantage studies
Can we track (generalized) objects that do
not move through real space, but move
through some other property space?
Observers can track non-spatial
‘virtual objects’ that move
through a ‘property space’:
Tracking superimposed surfaces
Two superimposed
Gabor patches that
vary in spatial
frequency, color and
angle
Blaser, Pylyshyn & Holcombe (2000)
Changing feature dimensions
Surfaces move randomly
in “feature-space”
Snapshots
snapshots taken every 250 ms
Such generalized ‘objects’ can be tracked
individually, and they also show single-object
superiority for change detection.
Some speculations about what vision
needs and what the vision module
may provide (1)
1. We need a mechanism that puts us in
causal contact with distal objects in a
visual scene – a contact that does not
depend on the object satisfying a certain
(conceptual) description, but on a brute
causal connection.
 We need such a connection in order to
connect vision and action.
 We need such a connection in order to ground
concepts to their instances.*
Speculations on what vision needs and
what the visual module may provide (2)
2. We need a mechanism that keeps track of the
identity of distal objects without using their
encoded properties – this happens whenever the
correspondence problem is solved.
 Such a mechanism realizes a rudimentary identitytracker, with its own internal ‘rules’.
3. This is not a general identity-maintenance
process; it will not allow you to recognize the
identity of a person in a picture and a person on
the street. But it may provide a way to maintain
same-objecthood within the modular early vision
system. There is also this tantalizing fact …
 There is evidence for such a mechanism in babies as
young as 4 months (Leslie, Spelke)!
Relation to work on infants’ sensitivity
to the cardinality of sets of objects
Alan Leslie’s “Object Indexes”
Infants as young as 4 months of age show surprise (longer
looking time) when they watch two things being placed behind
a screen and when the screen is lifted it reveals only one thing.
Below 10 months of age they are in general not surprised when
the screen is lifted to reveal two things that are different from
the ones they saw being placed behind the screen, so long as
their numerosity is correct.
In some cases, infants (age 10 months) use the difference in
color of the objects they are shown one-at-a-time to infer their
numerosity, but they do not record the colors and use them to
identify the objects that are revealed when the screen is lifted.
Leslie & Tremoulet: Infants aged 10 and 12 months are shown a red and then a green object that are then
hidden behind a screen. The 10 month old is surprised if raising the screen reveals the wrong number of
objects, not if it reveals the wrong color of objects. Color is used to individuate objects, but not to keep
track of them! At 12 months children can use color to keep track of what went behind the screen.
Some related trends in artificial
intelligence: Situated Robots
 AI has embraced (indeed, has in some cases been
overcome by) a recognition of the need for a
special indexical relation between representations
and the world. While some of this “situated”
movement has become a fad, there is an
important point behind the situated movement,
and it is the same point the Visual Index theory
has been making: We need some nonconceptual
connections between representations and things.
Forms of representation for a robot: using indexicals
Pylyshyn, Z.W. (2000). Situating vision on the world.
Trends in Cognitive Sciences, 4(5), 197-207
Indexes play a role very similar to that of demonstratives.
Are demonstratives essential for characterizing beliefs
and for explaining the connection between beliefs and
actions? Here is an example due to John Perry*:
“The author of the book Hiker’s Guide to the Desolation
Wilderness stands in the wilderness beside Gilmore Lake,
looking at the Mt. Tallac trail as it leaves the lake and climbs
the mountain. He desires to leave the wilderness. He
believes that the best way out from Gilmore Lake is to follow
the Mt. Tallac trail up the mountain … But he doesn’t move.
He is lost. He is not sure whether he is standing beside
Gilmore Lake, looking at Mt. Tallac, or beside Clyde Lake,
looking at the Maggie peaks. Then he begins to move along
the Mt. Tallac trail. If asked, he would have to explain the
crucial change in his beliefs in this way: ‘I came to believe
that this is the Mt. Tallac trail and that is Gilmore Lake’.”
* Perry, J. The problem of the essential indexical. In Themes from Kaplan (eds.
Almog, J., Perry, J. & Wettstein, H.) (Oxford University Press, New York, 1989).
Perry’s example is intended to show that in order to
understand and explain the action of the lost author
it is essential to use demonstratives such as this and
that in expressing the author’s beliefs.
A unique description of the Mt. Tallac trail
might help bring the person to the right belief,
but the problem of connecting the belief to an
action would remain unsolved until the person
had a deictic or demonstrative thought such as:
“That is the Mt. Tallac trail.”
or perhaps,
“The trail I am now looking at is the Mt. Tallac
trail”
Summary: FINSTs keep us
connected with the world
Selected references related to this talk
•Annan, V., & Pylyshyn, Z. W. (2002). Can indexes be
voluntarily assigned in multiple object tracking? Paper
presented at Vision Sciences 2002, Sarasota, FL.
•Ballard, D. H., Hayhoe, M. M., Pook, P. K., & Rao, R. P. N.
(1997). Deictic codes for the embodiment of cognition.
Behavioral and Brain Sciences, 20(4), 723-767.
•Blaser, E., Pylyshyn, Z. W., & Holcombe, A. O. (2000).
Tracking an object through feature-space. Nature, 408(9), 196199.
•Burkell, J., & Pylyshyn, Z. W. (1997). Searching through
subsets: A test of the visual indexing hypothesis. Spatial Vision,
11(2), 225-258.
•Dawson, M., & Pylyshyn, Z. W. (1988). Natural constraints in
apparent motion. In Z. W. Pylyshyn (Ed.), Computational
Processes in Human Vision: An interdisciplinary perspective
(pp. 99-120). Stamford, CT: Ablex Publishing.
•Intriligator, J., & Cavanagh, P. (2001). The spatial resolution of
attention. Cognitive Psychology, 4(3), 171-216.
•Leslie, A. M., Xu, F., Tremoulet, P. D., & Scholl, B. J. (1998).
Indexing and the object concept: Developing `what' and `where'
systems. Trends in Cognitive Sciences, 2(1), 10-18.
•Nissen, M. J. (1985). Accessing features and objects: Is location
special? In M. I. Posner & O. S. Marin (Eds.), Attention and
performance XI (pp. 205-219). Hillsdale, NJ: Lawrence
Erlbaum.
•Pylyshyn, Z. W. (1989). The role of location indexes in spatial
perception: A sketch of the FINST spatial-index model.
Cognition, 32, 65-97.
•Pylyshyn, Z. W. (1994). Some primitive mechanisms of spatial
attention. Cognition, 50, 363-384.
• Pylyshyn, Z. W. (2000). Situating vision in the world. Trends in
Cognitive Sciences, 4(5), 197-207.
• Pylyshyn, Z. W. (2001). Visual indexes, preconceptual objects, and
situated vision. Cognition, 80(1/2), 127-158.
• Pylyshyn, Z. W. (submitted). Tracking without keeping track: some
puzzling findings concerning multiple object tracking.
• Pylyshyn, Z. W., Burkell, J., Fisher, B., Sears, C., Schmidt, W., &
Trick, L. (1994). Multiple parallel access in visual attention.
Canadian Journal of Experimental Psychology, 48(2), 260-283.
• Pylyshyn, Z. W., & Storm, R. W. (1988). Tracking multiple
independent targets: evidence for a parallel tracking mechanism.
Spatial Vision, 3(3), 1-19.
• Scholl, B. J., & Pylyshyn, Z. W. (1999). Tracking multiple items
through occlusion: Clues to visual objecthood. Cognitive
Psychology, 38(2), 259-290.
• Scholl, B. J., Pylyshyn, Z. W., & Feldman, J. (2001). What is a
visual object: Evidence from target-merging in multiple-object
tracking. Cognition, 80, 159-177.
• Scholl, B. J., Pylyshyn, Z. W., & Franconeri, S. L. (submitted). The
relationship between property-encoding and object-based
attention: Evidence from multiple-object tracking.
• Sears, C. R., & Pylyshyn, Z. W. (2000). Multiple object tracking
and attentional processes. Canadian Journal of Experimental
Psychology, 54(1), 1-14.
• Tipper, S., Driver, J., & Weaver, B. (1991). Object-centered
inhibition of return of visual attention. Quarterly Journal of
Experimental Psychology, 43A, 289-298.
Appendix: Some other findings concerning
object tracking (1)
 Detection of events on targets is better than on
nontargets, but this does not generalize to locations
between targets;
 Objects can continue to be tracked when they
disappear completely behind occluders, as long as the
mode of disappearance is compatible with there
being an occluding surface;
 Objects can all disappear from view for as long as
330 ms without impairing tracking;
 When objects disappear behind an occluder and
come out a different color or shape, the change is
unnoticed;
Appendix: Some other findings
concerning object tracking (2)
 Not all distinct feature clusters can be tracked; some,
like the endpoints of a line, cannot;
 People can track items that automatically attract
attention, or they can decide which items to track;
but in the latter case it appears that the may have to
visit each object serially
 Successful tracking of an object entails keeping track
of it as a particular individual, yet people are poor at
keeping track of which successfully tracked (initially
numbered) item is which. This may be because:
 When observers make errors, they are more likely to switch
the identity of a target with that of another target than the
identity of a target with that of a nontarget.
The whole truth about multiple
object tracking
And many more demos ….
How do we do it? What properties of
individual objects do we use?
 MOT with occlusion
 MOT with Virtual Occluders
 MOT with implosion/explosion
 MOT MOT of the endpoints of a line
 MOT squares with rubber band connections
 MOT with IDs (which is which?)
 Track non-flashed (3 blinks)
 Track Non-flashed (one flash)
Ballard, Hayhoe et al.’s proposal
for a “deictic strategy”
Observers appear to use their direction-of-gaze as
their reference point in encoding patterns and
would prefer to make more eye movements rather
than devote extra effort to memorizing a simple
pattern.
Ballard, Hayhoe, Pook & Rao (1997):
“deictic codes and embodied cognition” BBS
Use of deictic pointers in the Ballard et al. study
Instead of taking only four glances at the model, which is all that is needed to
encode and copy subpatterns of only two blocks, subjects made 18 fixations into the
model and did not memorize more than they needed for the next basic action. The
most common sequence was: fixate model; fixate and pickup block; fixate model;
fixate workspace and drop off block (M-P-M-D). This strategy of using where the
eye points to as the focus for the memory representation might be seen as inefficient
from the perspective of the number of eye movements required, but it appears to be
more efficient from the point of view of the memory cost and illustrates the habitual
use of a deictic strategy wherein pointing into a real scene take precedence over
memorization (at least at the beginning of a block of trials). Ballard et al. concluded
that “subjects use fixation as a deictic pointing device to serialize the task and allow
incremental access to the immediately task-relevant information” and add, “Rather
than… a limitation on processing capacity, it can be seen as a necessary feature of a
system that makes dynamic use of deictic variables”. This conclusion is in agreemen
with the visual index theory which also suggested that the bottleneck in visual
processing may lie not in the capacity of short-term memory, but in the number of
variable bindings between objects and cognitive symbols that can be made using
visual indexes.