This course presents
an information-theoretic perspective on
visual form perception. The first lecture provides a general
introduction
to research on visual form, and a motivated positioning of the
information-theoretic perspective in this field of research. The second
and fourth lectures are theory-oriented, with an emphasis on
theoretical foundations of modeling principles such as pattern encoding
and the information-theoretic notion of simplicity. The third and fifth
lectures are model-oriented, with an emphasis on the development and
application of structural models of pattern completion and regularity
detection.
1. Visual
Form Perception
The problems of ambiguity,
viewpoint-dependence, and
veridicality
Goal, method, and means of visual information processing
Data-driven versus knowledge-driven perception
Hypothesis-testing models versus feature-integration models
Required Readings
Palmer, S. E. (1999). Theoretical approaches to vision. In S. E.
Palmer,
Vision Science: Photons to Phenomenology
(Chapter 2,
pp. 45-92). Cambridge, MA: MIT Press.
Optional Readings
Kanizsa, G. (1985). Seeing and thinking.
Acta Psychologica,
59
, 23-33.
2.
Structural Approaches
Structural classification and pattern encoding
Measuring code complexity
Emergent versus pre-set primitives
Regularity and hierarchy as determinants of structure
Required Readings
Leeuwenberg, E. L. J., & van der Helm, P. A. (1991). Unity and
variety in visual form.
Perception, 20, 595-622.
Optional Readings
Biederman, I. (1987). Recognition-by-components: A theory of human
image understanding.
Psychological Review, 94,
115-147.
3. The
Role of Viewpoint in Visual Occlusion
Nonaccidental properties and the General Viewpoint
assumption
Modeling visual pattern completion: shape + position
Required Readings
van Lier, R. J., van der Helm, P. A., & Leeuwenberg, E.
L. J. (1994). Integrating global and local aspects of visual occlusion.
Perception, 23, 883-903.
Optional Readings
Tarr, M. J., & Buelthoff, H. H. (1998). Image-based object
recognition in man, monkey and machine. In M. J. Tarr & H. H.
Buelthoff (Eds.),
Object recognition in man, monkey, and
machine
(pp. 1-20). Cambridge, MA: MIT Press.
4.
Simplicity Versus Likelihood
Classical, algorithmic, and structural information theory:
The
relation between probability and information.
The veridicality of simplicity: Occam versus Bayes
Required Readings
van der Helm, P. A. (2000). Simplicity versus likelihood in
visual perception: From surprisals to precisals.
Psychological
Bulletin, 126 , 770-800.
Optional Readings
Pomerantz, J., & Kubovy, M. (1986). Theoretical approaches to
perceptual organization: Simplicity and likelihood principles. In K. R.
Boff, L. Kaufman, & J. P. Thomas (Eds.),
Handbook of
perception and human performance: Vol. 2. Cognitive processes and
performance (pp. 36-1-36-46). New York: Wiley.
5.
Symmetry Perception
The internal structure of visual regularities
Weight of evidence as measure of detectability
Regularity detection: symmetry effects, number effects, salience
effects
Required Readings
van der Helm, P. A., & Leeuwenberg, E. L. J. (1996). Goodness
of
visual regularities: A nontransformational approach.
Psychological
Review, 103 , 429-456.
Optional Readings
Wagemans, J. (1999). Toward a better approach to goodness: Comments on
van der Helm and Leeuwenberg (1996).
Psychological Review,
106
, 610-621.
van der Helm, P. A., & Leeuwenberg, E. L. J. (1999). A better
approach to goodness: Reply to Wagemans (1999).
Psychological
Review, 106 , 622-630.
Small
groups
Elaboration and discussion on paradigmatic controversies in
visual form research:
1. Human versus machine vision
2. Perception versus recognition
3. Perceptual versus cognitive pattern completion
4. General-purpose versus special-purpose vision
5. Evolutionary perspectives
Assessment
I propose that students who desire credits write
a 10 page paper describing how the information-theoretic ideas are
relevant to their interests.
Peter van der Helm
Peter A. van der Helm received his Masters in Applied
Mathematics from the University of Twente (The Netherlands), and his
Ph.D. in Social Sciences from the University of Nijmegen (The
Netherlands). In 1983, he joined the Nijmegen Institute for Cognition
and Information (NICI) at the University of Nijmegen, where he is now
Associate Professor of Perception in the Department of Psychology. In
close cooperation with Emanuel Leeuwenberg, who initiated the
Structural Information Theory
(SIT) on visual form, Van der Helm developed the so-called Holographic
Approach which provides not only a formal-theoretic foundation of SIT
but also a new paradigm for empirical research on the detectability of
visual regularities. He published his work in various papers in
Journal
of Mathematical Psychology,
Psychological
Review,
and
Psychological Bulletin.
Peter
A. van der Helm 