Skip to main content
SpringerLink
Log in

Representing three-dimensional structures for visual recognition

  • Published:
Artificial Intelligence Review Aims and scope Submit manuscript

Abstract

Three-dimensional (3-D) geometrical models provide the best representations for 3-D objects. Not all representation schemes are suitable, however, for computer-based visual recognition. This survey analyses the historical development of recognition-oriented models from points and lines, to surfaces and volumes. It also considers those aspects of the models that successfully promoted recognition, and suggests likely areas for future development.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Adler, M. (1975) Understanding Peanuts' Cartoons, Department of Artificial Intelligence Research Report, 13, University of Edinburgh.

  • Agin, G. J. (1972) Representation and description of curved objects, PhD thesis AIM-1973, Stanford AI Lab.

  • Ballard, D. H. & Brown, C. M. (1982) Computer Vision, Prentice-Hall, New Jersey.

    Google Scholar 

  • Barrow, H. G. & Popplestone, R. J. (1971) Relational descriptions. In: Picture Processing. (eds. B. Meltzer & D. Michie), Machine Intelligence 6, 377–396.

  • Barrow, H. G. & Tenebaum, J. M. (1976) MSYS: a system for reasoning about scenes. Stanford Research Institute Technical Note 121.

  • Baumgart, B. G. (1972) Winged edge polyhedron representations, STAN-CS-320, AIM-179, Stanford AI Lab.

  • Binford, T. O. (1971) Visual perception by computer, IEEE Conference on Systems and Control.

  • Boissonnat, J. D. & Faugeras, O. D. (1981) Triangulation of 3-D objects. Proceedings of the 7th International Joint Conference on Artificial Intelligence, 658–660.

  • Bolles, R. C., Horaud, P. & Hannah, M. J. (1983) 3-DPO: a three-dimensional part orientation system. Proceedings of the 8th International Joint Conference on Artificial Intelligence, 1116–1120.

  • Brooks, R. A. (1981) Symbolic reasoning among 3-D models and 2-D images. Artificial Intelligence, 17, 285–348.

    Google Scholar 

  • Cameron, S. A. (1984) Modelling solids in motion. PhD Thesis, Department of Artificial Intelligence, University of Edinburgh.

  • Duda, R. & Hart, P. (1970) Experiments in scene analysis. Stanford Research Institute report AI group Technical note 20. Project 8259.

  • Falk, G. (1972) Interpretation of imperfect line data as a three-dimensional scene. Artificial Intelligence, 3, 101–144.

    Google Scholar 

  • Faugeras, O. D. & Hebert, M. (1983) A 3-D recognition and positioning algorithm using geometric matching between primitive surfaces. Proceedings of the International Joint Conference on Artificial Intelligence, 996–1002.

  • Fisher, R. B. (1986) From surfaces to objects: recognizing objects using surface information and object models, PhD Thesis, University of Edinburgh.

  • Hanson, A. & Riseman, E. (1978) VISIONS: a computer system for interpreting scenes. In: Computer Vision Systems, (eds. A. Hanson & E. Riseman) pp. 303–333. Academic Press, New York.

    Google Scholar 

  • Hogg, D. (1983) Model-based vision: a program to see a walking person. Image and Vision Computing, 1, 5–20.

    Google Scholar 

  • Marr, D. (1976) Representation and recognition of the spatial organization of three-dimensional objects. Massachusetts Institute of Technology AI memo 377.

  • Marr, D. (1982) Vision, W.H. Freeman & Co., San Francisco.

    Google Scholar 

  • Minsky, M. (1975) A framework for representing knowledge. In: The Psychology of Computer Vision, (ed. P. Winston) pp. 211–277. McGraw-Hill, New York.

    Google Scholar 

  • Nagao, M., Matsuyama, T. & Mori, H. (1979) Structural analysis of complex aerial photographs. Proceedings of the 6th International Joint Conference on Artificial Intelligence, 610–616.

  • Ohta, Y., Kanade, T. & Sakai, T. (1979) A production system for region analysis. Proceedings of the 6th International Joint Conference on Artificial Intelligence. pp. 684–686.

  • Requicha, A. A. G. & Voelcker, H. B. (1977) Constructive solid geometry. University of Rochester, Production Automation Project memo TM-25.

  • Roberts, L. G. (1965) Machine perception of three-dimensional solids. In: Optical and Electro-Optical Information Processing, (ed. J. T. Tippett) Ch. 9, p. 159–197. MIT Press, Cambridge, MA.

    Google Scholar 

  • Shapiro, L., Moriarty, J., Mulgaonkar, P. & Haralick, R. (1980) Sticks, plates and blobs: a three-dimensional object representation for scene analysis, NCAI-80.

  • Shirai, Y. (1978) Recognition of real-world objects using edge cue. In: Computer Vision Systems, (eds. A. Hanson & E. Riseman) pp. 353–362. Academic Press, New York.

    Google Scholar 

  • York, B. W., Hanson, A. R. & Riseman, E. M. (1981) 3-D object representation and matching with B-splines and surface patches. Proceedings of the 7th International Joint Conference on Artificial Intelligence, 648–651.

Download references

Author information

Authors and Affiliations

  1. Department of Artificial Intelligence, University of Edinburgh, EH1 2QL, Edinburgh, Scotland

    R. B. Fisher

Authors
  1. R. B. Fisher
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Fisher, R.B. Representing three-dimensional structures for visual recognition. Artif Intell Rev 1, 183–200 (1987). https://doi.org/10.1007/BF00142291

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00142291

Keywords

Search

Navigation