Abstract
The meaning of model and description is discussed in the framework of machine perception. An artificial intelligence perspective is adopted, viewing a model as a Knowledge Representation Language (KRL), and a description as a construct of a KRL. Generalised inference is a key feature, inextricably connected to all kinds of models. The latter are grouped into three basic schemes: relational, propositional and procedural, each of which motivated by the need to capture relevant aspects of perceptual tasks. The distinguishing features of the schemes are outlined. Profound links are emphasized between relational/structural and propositional/linguistic schemes, in analogy with mental representations in human beings. The need to further combine the schemes into unified, hybrid representation languages emerges as a trend in present and future research.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
D. Ballard and CM. Brown, Computer Vision, Prentice Hall, Englewood Cliffs, NY (1982).
R.A. Brooks, Intelligence without Representation, Artificial Intelligence, Vol.47, pp. 139–159 (1991).
R. Davis, H. Shrobe, and P. Szolovits, What Is a Knowledge Representation?, The AI Magazine, pp. 17-33 (1993).
D. Marr, Vision, Freeman, San Francisco, CA (1982).
M. Minsky, Logical Versus Analogical or Symbolic Versus Connectionist or Neat Versus Scruffy, The AI Magazine, pp. 34-51 (1991).
H. Niemann, G.F. Sagerer, S. Schröder, and F. Kümmert, ERNEST: A Semantic Network System for Pattern Understanding, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.12, No.9, pp. 883–905 (1990).
R. Reiter and A.K. Mackworth, A Logical Framework for Depiction and Image Interpretation, Artificial Intelligence, Elsevier Science Publishers, Vol.41, pp. 125–155 (1989/90).
J.J. Gibson, The Ecological Approach to Visual Perception, Houghton Mifflin, Boston, MA (1979).
J. Glasgow and D. Papadias, Computational Imagery, Cognitive Science, Vol.16, pp. 355–394 (1992).
J. Mylopoulos and H. Levesque, An Overview on Knowledge Representation, in On Conceptual Modelling: Perspectives from Artificial Intelligence, Databases and Programming Languages, M. Brodie, J. Mylopoulos, and J.V. Schmidt eds., Springer Verlag, New York, NY, pp. 3–17 (1983).
R.A. Frost, Introduction to Knowledge Base Systems, Collins, London, UK (1986).
M.R. Genesereth and N.J. Nilsson, Logical Foundations of Artificial Intelligence, Morgan Kaufmann, Los Altos, CA (1987).
G.D. Hager, Task-Directed Sensor Fusion and Planning, Kluwer, Boston, MA (1990).
R.C. Luo and M.G. Kay, Multisensor Integration and Fusion in Intelligent Systems, IEEE Transactions on Systems, Man and Cybernetics, Vol.SMC-19, No.5, pp. 901–931 (1989).
J.L. Crowley and Y. Demazeau, Principles and Techniques for Sensor Data Fusion, in Signal Processing, special issue on Intelligent Systems for Signal and Image Understanding, V. Roberto ed., Elsevier Science Publishers, Vol.32, No.1-2, pp. 5–27 (1993).
E. Dickmanns, An Integrated Approach to Feature Based Dynamic Vision, Proceedings of the International Conference on Computer Vision and Pattern Recognition, Ann Arbor, MI (1988).
R.S. Engelmore and A.J. Morgan eds., Blackboard Systems, Addison Wesley, Wokingham, UK (1988).
F. Hayes-Roth, D.A. Waterman, and D.B. Lenat, Principles of Pattern-Directed Inference Systems, in Pattern-Directed Inference Systems, D.A. Waterman and F. Hayes-Roth eds., Academic Press, New York, NY, pp. 577–601 (1978).
G. Agha, Actors: a Model of Concurrent Computation in Distributed Systems, MIT Press, Cambridge, MA (1986).
C. Hewitt and J. Inman, DAI Betwixt and Between: from “Intelligent Agents” to Open Systems Science, IEEE Transactions on Systems, Man, and Cybernetics, Vol.21, No.6, pp. 1409–1419 (1991).
A. Pentland, Perceptual Organization and the Representation of Natural Form, Artificial Intelligence, Vol.28, pp. 293–331 (1986).
L.G. Shapiro and R.M. Haralick, Structural Descriptions and Inexact Matching, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.3, No.5, pp. 504–519 (1981).
J. Pearl, Probabilistic Reasoning in Intelligent Systems, Morgan Kaufmann, San Mateo, CA (1988).
R. Luccio, Gestalt Problems in Cognitive Psychology: Field Theory, Invariance and Auto-Organisation, in Intelligent Perceptual Systems, V. Roberto ed., Lecture Notes in AI, Springer-Verlag, Berlin, D, Vol.745, pp. 2–19 (1993).
K.S. Fu, Syntactic Pattern Recognition and Applications, Prentice Hall, Englewood Cliffs, NY (1982).
Y. Aloimonos, I. Weiss, and A. Bandyopadhyay, Active Vision, Proceedings of the First IEEE Conference on Computer Vision, pp. 35-54 (1987).
K. Bowyer and C.R. Dyer, Aspect Graphs: an Introduction and Survey of Recent Results, International Journal of Imaging Systems and Technology, John Wiley & Sons Ltd, Vol.2, pp. 315–328 (1990).
R. Quillian, Semantic Memory, in Semantic Information Processing, M. Minsky ed., MIT Press, Cambridge, MA (1968).
R.J. Brachman, What IS-A Is and Isn’t: An Analysis of Taxonomic Links in Semantic Networks, IEEE Computer, Vol.16, No.10, pp. 30–36 (1983).
M. Minsky, A Framework for Representing Knowledge, in The Psychology of Computer Vision, P.H. Winston ed., McGraw Hill, New York, NY, pp. 211–277 (1985).
V. Roberto, Perceptual and Conceptual Representations in a Geophysical Image-Understanding System, in Proceedings of the 6th International Conference on Image Analysis and Processing, V. Cantoni, M. Ferretti, S. Levialdi, R. Negrini, and R. Stefanelli eds., World Scientific Publishing Ltd, Singapore, pp. 713–720 (1992).
D.G. Bobrow and T. Winograd, An Overview of KRL, a Knowledge Representation Language, Cognitive Science, Vol.1, No.1, pp. 3–46 (1977).
R. Fikes and T. Kehler, The Role of Frame-Based Representation in Reasoning, Communications of the ACM, Vol.28, No.9, pp. 904–920 (1985).
R.J. Brachman and J.G. Schmölze, An Overview of the KL-ONE Knowledge Representation System, Cognitive Science, Vol.9, pp. 171–216 (1985).
E. Ardizzone, S. Gaglio, and F. Sorbello, Geometric and Conceptual Knowledge Representation within a Generative Model of Visual Perception, Journal of Intelligent and Robotic Systems, Kluwer Academic Publishers, Vol.2, pp. 381–409 (1989).
L. Zadeh, Fuzzy Sets and Systems, Elsevier, Amsterdam, NL (1983).
A. Deliyanni and R.A. Kowalski, Logic and Semantic Networks, Communications of the ACM, Vol.22, No.3, pp. 184–192 (1979).
P.J. Hayes, The Logic of Frames, in Frame Conceptions and Text Understanding, D. Metzing, W. De Gruyter and Co. ed., Berlin, D, pp. 46-61 (1979).
W. Wahlster, E. Andrè, W. Graf, and T. Rist, Knowledge-Based Media Coordination in Intelligent User Interfaces, in Trends in Artificial Intelligence, E. Ardizzone, S. Gaglio, and F. Sorbello eds., Springer-Verlag, Berlin, D, pp. 2–16 (1991).
S.K. Chang, Principles of Pictorial Information System Design, Prentice Hall, Englewood Cliffs, NY (1989).
J.R.J. Shirra, G. Bosch, C.K. Sung, and G. Zimmermann, From Image Sequences to Natural Language: A First Step Toward Automatic Perception and Description of Motions, Applied Artificial Intelligence, Vol.1, pp. 287–305 (1987).
V. Roberto and C. Chiaruttini, Seismic Signal Understanding: a Knowledge-Based Recognition System, IEEE Transactions on Signal Processing, Vol.40, No.7, pp. 1787–1806 (1992).
R.A. Brooks, Model-Based Three-Dimensional Interpretations of Two-Dimensional Images, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.5, No.2, pp. 140–150 (1983).
D.M. McKeown, W.A. Harvey, and J. McDermott, Rule-Based Interpretation of Aerial Imagery, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.7, No.5, pp. 570–585 (1985).
V. Roberto, Knowledge-Based Understanding of Signals: an Introduction, in Signal Processing, special issue on Intelligent Systems for Signal and Image Understanding, V. Roberto ed., Vol.32, No. 1-2, pp. 5–27 (1993).
M. Nagao, T. Matsuyama, and H. Mori, Structural Analysis of Complex Aerial Photographs, in Blackboard Systems, R.S. Engelmore and A.J. Morgan eds., Addison Wesley Publishers Ltd, Wokingham, UK, pp. 219–230 (1988).
P.N. Johnson-Laird, Semantic Primitives Or Meaning Postulates: Mental Models Or Propositional Representations?, in Computational Models of Natural Language Processing, B. Bara and G. Guida eds., Elsevier, Amsterdam, NL, pp. 227–243 (1984).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1994 Springer Science+Business Media New York
About this chapter
Cite this chapter
Roberto, V. (1994). Models and Descriptions in Machine Vision. In: Cantoni, V. (eds) Human and Machine Vision. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-1004-2_17
Download citation
DOI: https://doi.org/10.1007/978-1-4899-1004-2_17
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4899-1006-6
Online ISBN: 978-1-4899-1004-2
eBook Packages: Springer Book Archive