Robot Vision pp 129-142 | Cite as

Towards a Flexible Vision System

  • O. D. Faugeras
  • F. Germain
  • G. Kryze
  • J. D. Boissonnat
  • M. Herbert
  • J. Ponce
  • E. Pauchon
  • N. Ayache
Part of the International Trends in Manufacturing Technology book series (MANUTECH)

Abstract

A Vision System designed for building accurate models of industrial parts is described. Potential applications include tolerancing testing, data base acquisition and automatic recognition of objects. The system is made of a laser rangefinder that measures the position in space of points on the parts by active stereoscopy, a table on which the parts are positioned and can be translated vertically and rotated under computer control, and a set of algorithms to produce accurate geometric models of the part based on the measurements made by the laser. Representation and recognition results are presented on a variety of objects as shaded graphics displays.

Keywords

Retina Expense Hull 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    J. D. Boissonnat and F. Germain, ‘A New Approcah to the Problem of Acquiring Randomly Oriented Workpieces out of a Bin’, Proc. 7th Int. Joint Conf. On Artificial Intelligence, pp. 796–802 (1981).Google Scholar
  2. [2]
    T. O. Binford, ‘Visual Perception by Computer’, IEEE Conf. on Systems and Control, Miami (December 1971).Google Scholar
  3. [3]
    G. J. Agin and T. O. Binford, ‘Computer Description of Curved Objects’, Proc. 3rd Int. Joint Conf. on Artificial Intelligence,pp. 629–640.Google Scholar
  4. [4]
    R. Nevatia and T. O. Binford, ‘Description and Recognition of Curved Objects’, Artificial Intelligence, Vol. 8, pp. 77–98 (1977).MATHCrossRefGoogle Scholar
  5. [5]
    R. K. Bajcsy and B. I. Soroka, ‘Steps towards the Representation of Complex Three-Dimensional Objects’, Proc. 5th Int. Joint Conf. on Artificial Intelligence,pp. 596.Google Scholar
  6. [6]
    D. Marr, ‘Representing Visual Information — A Computational Approach’, in Computer Vision Systems, A. R. Hanson and E. M. Riseman (Eds.), pp. 61–80, Academic Press (1978).Google Scholar
  7. [7]
    N. Badler and R. Bajcsy, ‘Three-Dimensional Representation for Computer Graphics and Computer Vision’, ACM Computer Graphics, Vol. 12, pp. 153–160 (August 1978).CrossRefGoogle Scholar
  8. [8]
    M. Oshima and Y. Shirai, ‘A Scene Description Method Using Three-Dimensional Information’, Pattern Recognition, Vol. 11, pp. 9–17 (1978).CrossRefGoogle Scholar
  9. [9]
    Y. Shirai, ‘On Application of 3-Dimensional Computer Vision’, Bul. Electrotech. Lab., Vol. 43, No. 6 (1979).Google Scholar
  10. [10]
    Y. Shirai, ‘Use of Models in Three-Dimensional Object Recognition’, in Man-Machine Communication in CAD/CAM, T. Sata, E. Warman (Eds.), North-Holland Publishing Company (1981).Google Scholar
  11. [11]
    B. Bhanu, ‘Shape Matching and Image Segmentation Using Stochastic Labelling’, Ph.D Dissertation, University of Southern California, Los Angeles, August 1981.Google Scholar
  12. [12]
    D. T. Lee and B. J. Schacter, ‘Two Algorithms for Constructing a Delaunay Triangulation, Int. Journal ofComp. And Inf. Sciences, Vol. 9, No. 3 (1980).Google Scholar
  13. [13]
    F. P. Preparata and S. J. Hong, ‘Convex Hulls of Finite Sets of Points in Two and Three Dimensions’, Comm. ACM, Vol. 20, No. 2 (1977).Google Scholar
  14. [14]
    D. Hilbert and S. Cohn Vossen, Geometry and Imagination,Chelsea.Google Scholar
  15. [15]
    J. L. Bentley, J. H. Friedman, ‘Fast Algorithms for Constructing Minimal Spanning Trees in Coordinate Spaces’, IEEE Trans. Comp., Vol. C-27, No. 2 (February 1978).Google Scholar
  16. [16]
    J. D. Boissonnat and O. D. Faugeras, ‘Triangulation of 3-D Objects’, Proc. 7th Int. Joint Conf. on Artificial Intelligence, pp. 658–660 (1981).Google Scholar
  17. [17]
    L. Kitchen and A. Rosenfeld, ‘Discrete Relaxation for Matching Relational Structures’, IEEE Trans. Systems, Man and Cybernetics, Vol. SMC-9, pp. 869–874 (Dec. 1979).Google Scholar
  18. [18]
    L. Kitchen, ‘Relaxation Applied to Matching Quantitative Relational Structures’, IEEE Trans. Systems, Man and Cybernetics, Vol. SMC-10, pp. 96–101 (February 1980).Google Scholar
  19. [19]
    R. M. Haralick and L. G. Shapiro, ‘The Consistent Labelling Problem, Part I’, IEEE Trans. Pattern Anal. Machine Intell., Vol. PAMI-I, pp. 173–184 (April 1979).Google Scholar
  20. [20]
    R. M. Haralick and L. G Shapiro, ‘The Consistent Labelling Problem, Part II’, IEEE Trans. Pattern Anal. Machine Intell., Vol. PAMI-2, pp. 193–203 (May 1980).Google Scholar
  21. [21]
    O. D. Faugeras and K. Price, ‘Semantic Description of Aerial Images Using Stochastic Labelling’, IEEE Trans, Pattern Anal. Machine Intell., Vol. PAMI-, pp. (November 1981).Google Scholar
  22. [22]
    O. D. Faugera and M. Berthod, ‘Scene Labelling: an Optimization Approach’, IEEE Trans. Pattern Anal. Machine Intell., Vol. PAMI-, pp. (1981).Google Scholar
  23. [23]
    M. Hebert and J. Ponce, ‘A New Method For Segmenting 3-D Scenes’. I.C.P.R. (October 1982).Google Scholar
  24. [24]
    J.Serra, Image Analysis and Mathematical Morphology,Academic Press (1981).Google Scholar
  25. [25]
    E. Pauchon, These de Docteur Ingenieur, Universite d’Orsay, 1983, to appear.Google Scholar
  26. [26]
    N. Ayache, ‘Reconnaissance d’objets 2-D parteillement caches’, These de Docteur Ingenieur, Universite d’Orsay, to appear December 1982.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1983

Authors and Affiliations

  • O. D. Faugeras
    • 1
  • F. Germain
    • 1
  • G. Kryze
    • 1
  • J. D. Boissonnat
    • 1
  • M. Herbert
    • 1
  • J. Ponce
    • 1
  • E. Pauchon
    • 1
  • N. Ayache
    • 1
  1. 1.INRIA Domaine de Voluceau-RocquencourtFrance

Personalised recommendations