Panel Summary Looking For Visual Primitives

  • Carlo Arcelli
  • Luigi P. Cordella
  • Leila De Floriani


Visual primitives can be considered as abstractions of those informative subsets of an image which are of interest in a given vision task. After discussing their nature and some problems related to their extraction, pattern description in terms of primitives is considered. Eventually, models relating 3-D visual primitives in high level vision are discussed.


Object Recognition Boundary Model Primitive Feature Good Continuation Primitive Component 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    H.B. Barlow, R. Narasimhan, and A. Rosenfeld, Visual pattern analysis in machines and animals Science, Vol.177, pp. 567–575 (1972).PubMedCrossRefGoogle Scholar
  2. 2.
    T. Pavlidis, Structural Pattern Recognition, Springer-Verlag, Berlin, D (1977).Google Scholar
  3. 3.
    K.S. Fu, Syntactic Methods in Pattern Recognition, Academic Press, New York, NY (1974).Google Scholar
  4. 4.
    K. Fukunaga, Introduction to Statistical Pattern Recognition, Academic Press, New York, NY (1972).Google Scholar
  5. 5.
    P. Devijver and J. Kittler, Pattern Recognition: a Statistical Approach, Prentice-Hall, Englewood Cliffs, NJ (1982).Google Scholar
  6. 6.
    R.M. Bolle, A. Califano, and R. Kjeldsen, A complete and extendable approach to visual recognition, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.14, pp. 534–548 (1992).CrossRefGoogle Scholar
  7. 7.
    R. Narasimhan, On the description, generation, and recognition of classes of pictures, in Automatic Interpretation and Classification of Images, A. Grasselli ed., Academic Press, New York, NY, pp. 1–42 (1969).Google Scholar
  8. 8.
    E.J. Gibson, H. Osser, W. Schiff, and J. Smith, An analysis of cirtical features of letters, tested by a confusion matrix, in A Basic Research Program on Reading, Cooperative Research Project No. 630, U.S. Office of Education (1963).Google Scholar
  9. 9.
    D. Marr and E. Hildreth, Theory of edge detection, Proc. of the Royal Society, B, Vol.207, pp. 187–217 (1980).CrossRefGoogle Scholar
  10. 10.
    K. Koffka, Principles of Gestalt Psychology, Harcourt-Brace, New York, NY (1963).Google Scholar
  11. 11.
    G. Kanizsa, Organization in Vision, Essays on Gestalt Perception, Praeger Special Studies, Praeger, New York, NY (1979).Google Scholar
  12. 12.
    T. Pavlidis and Y.T. Liow, Integrating region growing and edge detection, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.12, pp. 225–233 (1990).CrossRefGoogle Scholar
  13. 13.
    A.C. Shaw, A formal picture description scheme as a basic for picture processing systems, Information and Control, Vol.14, pp. 9–52 (1962).CrossRefGoogle Scholar
  14. 14.
    R.S. Ledley et al., FIDAC: film input to digital automatic computer and associated sintax-directed pattern recognition programming system, in Optical and Electro-Optical Information Processing, chapt.33, MIT Press, Cambridge, pp. 591–614 (1965).Google Scholar
  15. 15.
    S.J. Dickinson, A. Rosenfeld, and A.P. Pentland, Primitive-based shape modeling and recognition, in Visual Form: Analysis and Recognition, Plenum Press, New York, NY, pp. 213–229 (1992).Google Scholar
  16. 16.
    M.D. Levine, R. Bergevin, and Q.L. Nguyen, Shape description using geons as 3D primitives, in Visual Form: Analysis and Recognition, Plenum Press, New York, NY, pp. 363–377 (1992).Google Scholar
  17. 17.
    P.J. Flynn and A.K. Jain, CAD-based Computer Vision: From CAD Models to Relational Graphs, IEEE Trans, on Pattern Analysis and Machine Intelligence, Vol.13, No.2, pp. 114–132 (1991).CrossRefGoogle Scholar
  18. 18.
    P.J. Besl and R.C. Jain, Three-dimensional object recognition, ACM Comput. Surveys, Vol. 17, No. 1, pp. 75–145 (1985).CrossRefGoogle Scholar
  19. 19.
    R.T. Chin and C.R. Dyer, Model-based recognition in robot vision, ACM Comput. Surveys, Vol.18, No.1, pp. 67–108 (1986).CrossRefGoogle Scholar
  20. 20.
    J. Brady, N. Nandhakumar, and J. Aggarwal, Recent progress in the recognition of objects from range data, Proceedings 9th Int. Conf. Pattern Recognition, pp. 85-92 (1988).Google Scholar
  21. 21.
    C. Hansen and T.C. Henderson, CAGD-based Computer Vision, IEEE Trans, on Pattern Analysis and Machine Intelligence, Vol.11, No.11, pp. 1181–1193 (1989).CrossRefGoogle Scholar
  22. 22.
    I. Biederman, Human Image Understanding: Recent Research and a Theory, Computer Vision, Graphics and Image Processing, Vol.32, pp. 29–73 (1985).CrossRefGoogle Scholar
  23. 23.
    A. Chianese, L.P. Cordella, M. De Santo, and M. Vento, Classifying character shapes, in Visual Form: Analysis and Recognition, Plenum Press, New York, NY, pp. 155–164 (1992).Google Scholar
  24. 24.
    A.L. Yarbus, Eye Movements and Vision, Plenum Press, New York, NY (1967).Google Scholar
  25. 25.
    D.J. Felleman and D.C. Van Essen, Distributed hierarchical processing in the primate cerebral cortex, Cerebral Cortex, Vol.1, pp. 1–47 (1991).PubMedCrossRefGoogle Scholar
  26. 26.
    L.G. Ungerleider and M. Mishkin, Two cortical visual systems, in Analysis of Visual Behaviour, MIT Press, Cambridge, pp. 549–586 (1982).Google Scholar
  27. 27.
    M. Corbetta, F.M. Miezin, S. Dobmeyer, G.L. Shulman, and S.E. Petersen, Attentional modulation of neural processing of shape, colour and velocity in humans, Science, Vol.248, pp. 1556–1559 (1990).PubMedCrossRefGoogle Scholar
  28. 28.
    D.I. Perrett and M.W. Oram, Neurophysiology of shape processing, Image and Vision Computing, Vol.11, pp. 317–333 (1993).CrossRefGoogle Scholar
  29. 29.
    F. Attneave, Informational aspects of visual perception, Psychological Review, Vol.61, pp. 183–193 (1954).PubMedCrossRefGoogle Scholar
  30. 30.
    H. Blum, A transformation for extracting new descriptors of shape, in Models for the Perception of Speech and Visual Form, MIT Press, Cambridge, pp. 362–380 (1967).Google Scholar
  31. 31.
    A. Chianese, L.P. Cordella, M. De Santo, and M. Vento, Decomposition of ribbon-like shapes, Proc. 6th Scandinavian Conf on Image Analysis, Oulu, SF, pp. 416-423 (1989).Google Scholar
  32. 32.
    S. Zhang, G.D. Sullivan, and K.D. Baker, The Automatic Construction of a View-Independent Relational Model for 3-D Object Recognition, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.15, No.6, pp. 531–544 (1993).CrossRefGoogle Scholar
  33. 33.
    D. Marr and K.H. Nishihara, Representation and recognition of the spatial organization of three-dimensional shape, Proc. R. Soc. Lond., B, Vol.200, pp. 269–294 (1978).PubMedCrossRefGoogle Scholar
  34. 34.
    M.R. Korn and C.R. Dyer, 3-D multiview object representations for model-based recognition, Pattern Recognition, Vol. 20, No. 1, pp. 91–103 (1987).CrossRefGoogle Scholar
  35. 35.
    L. DeFloriani, Feature extraction from boundary models of three dimensional objects, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.11, No.8, pp. 785–798 (1989).CrossRefGoogle Scholar
  36. 36.
    A.K.C. Wong, S.W. Lu, and M. Rioux, Recognition and shape synthesis of 3D objects based on attributed hypergraphs, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 11, No.3, pp. 279–290 (1990).CrossRefGoogle Scholar
  37. 37.
    J.J. Koenderink and A.J. van Doom, The singularities of the visual mapping, Biol. Cybern., Vol.24, pp. 51–59 (1976).PubMedCrossRefGoogle Scholar
  38. 38.
    M. Pratt, Solid Modelling, Survey and Current Research Issues (1990).Google Scholar

Copyright information

© Springer Science+Business Media New York 1994

Authors and Affiliations

  • Carlo Arcelli
    • 1
  • Luigi P. Cordella
    • 2
  • Leila De Floriani
    • 3
  1. 1.Istituto di Cibernetica del CNRArco Felice (NA)Italy
  2. 2.Dipartimento di Informatica e SistemisticaUniversità di Napoli “Federico II”NapoliItaly
  3. 3.Dipartimento di Informatica e Scienze dell’InformazioneUniversità di GenovaGenovaItaly

Personalised recommendations