Shape, Contour and Grouping in Computer Vision pp 31-57

Part of the Lecture Notes in Computer Science book series (LNCS, volume 1681)

Shape Models and Object Recognition

  • Jean Ponce
  • Martha Cepeda
  • Sung-il Pae
  • Steve Sullivan
Chapter

Abstract

This paper discusses some problems that should be addressed by future object recognition systems.

In particular, there are things that we know how to do today, for example:
  1. 1.

    Computing the pose of a free-form three-dimensional object from its outline (e.g. [106]).

     
  2. 2.

    Identifying a polyhedral object from point and line features found in an image (e.g., [46, 89]).

     
  3. 3.

    Recognizing a solid of revolution from its outline (e.g., [59]).

     
  4. 4.

    Identifying a face with a fixed pose in a photograph (e.g., [10, 111]).

     

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References

  1. [1]
    G.J. Agin. Representation and description of curved objects. PhD thesis, Stanford University, Stanford, CA, 1972.Google Scholar
  2. [2]
    V.I. Arnol’d. Singularities of smooth mappings. Russian Math. Surveys, pages 3–44, 1969.Google Scholar
  3. [3]
    H. Asada and J.M. Brady. The curvature primal sketch. IEEE Trans. Patt. Anal. Mach. Intell., 8(1):2–14, 1986.Google Scholar
  4. [4]
    N. Ayache and O. Faugeras. Hyper: a new approach for the recognition and positioning of two-dimensional objects. IEEE Trans. Patt. Anal. Mach. Intell., 8(1):44–54, January 1986.Google Scholar
  5. [5]
    A.H. Barr. Superquadrics and angle preserving transformations. IEEE Computer Graphics and Applications, 1:11–23, January 1981.CrossRefGoogle Scholar
  6. [6]
    J. Barraquand and M. Berthod. A non-linear second order edge detector. In International Image Week, Second Image Symposium, Nice, France, 1986.Google Scholar
  7. [7]
    J. Barraquand, B. Langlois, and J.C. Latombe. Robot motion planning with many degrees of freedom and dynamic constraints. In Int. Symp. on Robotics Research, pages 74–83, Tokyo, Japan, 1989. Preprints.Google Scholar
  8. [8]
    R. Basri, D. Roth, and D. Jacobs. Clustering apperance of 3D objects. In Proc. IEEE Conf. Comp. Vision Patt. Recog., pages 414–420, Santa Barbara, CA, June 1998.Google Scholar
  9. [9]
    B.G. Baumgart. Geometric modeling for computer vision. Technical Report AIM-249, Stanford University, 1974. Ph.D. Thesis. Department of Computer Science.Google Scholar
  10. [10]
    P.N. Belhumeur, J.P. Hesphanha, and D.J. Kriegman. Eigengaces vs. Fisherfaces: recognition using class-specific linear projection. IEEE Trans. Patt. Anal. Mach. Intell., 19(7):711–720, 1997.CrossRefGoogle Scholar
  11. [11]
    R. Bergevin and M. Levine. Part decomposition of objects from single view line drawings. CVGIP: Image Understanding, 55(3):17–34, 1992.Google Scholar
  12. [12]
    I. Biederman. Human image understanding: Recent research and a theory. Comp. Vis. Graph. Im. Proc., 32(1):29–73, 1985.CrossRefGoogle Scholar
  13. [13]
    T.O. Binford. Visual perception by computer. In Proc. IEEE Conference on Systems and Control, 1971.Google Scholar
  14. [14]
    T.O. Binford. Body-centered representation and recognition. In M. Hebert, J. Ponce, T.E. Boult, and A. Gross, editors, Object Representation for Computer Vision, number 994 in Lecture Notes in Computer Science, pages 207–215. Springer-Verlag, 1995.Google Scholar
  15. [15]
    T.O. Binford and T.S. Levitt. Quasi-invariants: theory and applications. In Proc. DARPA Image Understanding Workshop, pages 819–829, 1993.Google Scholar
  16. [16]
    H. Blum. A transformation for extracting new descriptors of shape. In W. Wathen-Dunn, editor, Models for perception of speech and visual form. MIT Press, Cambridge, MA, 1967.Google Scholar
  17. [17]
    R.A. Brooks. Symbolic reasoning among 3-D models and 2-D images. Artificial Intelligence, 17(1-3):285–348, 1981.CrossRefGoogle Scholar
  18. [18]
    R.A. Brooks, R. Greiner, and T.O. Binford. Model-based three-dimensional interpretation of two-dimensional images. In Proc. International Joint Conference on Artificial Intelligence, pages 105–113, Tokyo, Japan, Aug. 1979.Google Scholar
  19. [19]
    J.W. Bruce, P.J. Giblin, and F. Tari. Parabolic curves of evolving surfaces. Int. J. of Comp. Vision, 17(3):291–306, 1996.CrossRefGoogle Scholar
  20. [20]
    B. Burns, R. Weiss, and E. Riseman. The non-existence of general-case viewinvariants. In Geometric Invariance in Computer Vision, pages 120–131. MIT Press, 1992.Google Scholar
  21. [21]
    M. Cepeda.Generalized cylinders revisited: theoretical results and preliminary implementation. Master’s thesis, Department of Computer Science, University of Illinois at Urbana-Champaign, 1998.Google Scholar
  22. [22]
    B. Chiyokura and F. Kimura. Design of solids with free-form surfaces. Computer Graphics, 17(3):289–298, Nov. 1983.CrossRefGoogle Scholar
  23. [23]
    D.T. Clemens and D.W. Jacobs. Model group indexing for recognition. IEEE Trans. Patt. Anal. Mach. Intell., 13(10):1007–1017, 1991.CrossRefGoogle Scholar
  24. [24]
    J.L Crowley and A.C. Parker. A representation of shape based on peaks and ridges in the difference of low-pass transform. IEEE Trans. Patt. Anal. Mach. Intell., 6:156–170, 1984.Google Scholar
  25. [25]
    S. Dickinson, A.P Pentland, and A. Rosenfeld. 3D shape recovery using distributed aspect matching. IEEE Trans. Patt. Anal. Mach. Intell., 14(2):174–198, 1992.CrossRefGoogle Scholar
  26. [26]
    R. Duda and P. Hart. Pattern classification and scene analysis. Wiley, 1973.Google Scholar
  27. [27]
    G. Eberly, R. Gardner, B. Morse, S. Pizer, and C. Scharlach. Ridges for image analysis. Technical report, Univ. of North Carolina, Dept. of Comp. Sc., 1993.Google Scholar
  28. [28]
    D. Eggert and K. Bowyer. Computing the orthographic projection aspect graph of solids of revolution. In Proc. IEEE Workshop on Interpretation of 3D Scenes, pages 102–108, Austin, TX, November 1989.Google Scholar
  29. [29]
    D. Eggert, K. Bowyer, C. Dyer, H. Christensen, and D. Goldgof. The scale space aspect graph. IEEE Trans. Patt. Anal. Mach. Intell., 15(11):1114–1130, 1993.CrossRefGoogle Scholar
  30. [30]
    G. Farin. Curves and Surfaces for Computer Aided Geometric Design. Academic Press, San Diego, CA, 1993.Google Scholar
  31. [31]
    O.D. Faugeras and M. Hebert. The representation, recognition, and locating of 3-D objects. International Journal of Robotics Research, 5(3):27–52, Fall 1986.CrossRefGoogle Scholar
  32. [32]
    D. Forsyth. Recognizing an algebraic surface from its outline. Int. J. of Comp. Vision, 18(1):21–40, April 1996.CrossRefMathSciNetGoogle Scholar
  33. [33]
    D.A. Forsyth and M.M. Fleck. Body plans. In Proc. IEEE Conf. Comp. Vision Patt. Recog., pages 678–683, San Juan, PR, June 1997.Google Scholar
  34. [34]
    J.M. Gauch and S.M. Pizer. Multiresolution analysis of ridges and valleys in grey-scale images. IEEE Trans. Patt. Anal. Mach. Intell., 15(6), June 1993.Google Scholar
  35. [35]
    Z. Gigus, J. Canny, and R. Seidel. Efficiently computing and representing aspect graphs of polyhedral objects. IEEE Trans. Patt. Anal. Mach. Intell., 13(6), June 1991.Google Scholar
  36. [36]
    W.E.L. Grimson and T. Lozano-Pérez. Localizing overlapping parts by searching the interpretation tree. IEEE Trans. Patt. Anal. Mach. Intell., 9(4):469–482, 1987Google Scholar
  37. [37]
    R.M. Haralick. Ridges and valleys in digital images. Comp. Vis. Graph. Im. Proc., 22:28–38, 1983.CrossRefGoogle Scholar
  38. [38]
    R.M. Haralick and L.G. Shapiro. Computer and robot vision. Addison Wesley, 1992.Google Scholar
  39. [39]
    R.M. Haralick, L.T. Watson, and T.J. Laffey. The topographic primal sketch. International Journal of Robotics Research, 2:50–72, 1983.CrossRefGoogle Scholar
  40. [40]
    C. Harris and M. Stephens. A combined edge and corner detector. In 4th Alvey Vision Conference, pages 189–192, Manchester, UK, 1988.Google Scholar
  41. [41]
    G. Healey and D. Slater. Global color constancy. J. Opt. Soc. Am. A, 11(11):3003–3010, 1994.Google Scholar
  42. [42]
    M. Hebert, J. Ponce, T.E. Boult, A. Gross, and D. Forsyth. Report on the NSF/ARPA workshop on 3D object representation for computer vision. In M. Hebert, J. Ponce, T.E. Boult, and A. Gross, editors, Object Representation for Computer Vision, Lecture Notes in Computer Science. Springer-Verlag, 1995. Also available through the World-Wide Web at the following address: //www.ius.cs.cmu.edu/usr/users/hebert/www/workshop/report.html.Google Scholar
  43. [43]
    D.D. Hoffman and W. Richards. Parts of recognition. Cognition, 18:65–96, 1984.CrossRefGoogle Scholar
  44. [44]
    J. Hollerbach. Hierarchical shape description of objects by selection and modi-fication of prototypes. AI Lab. TR-346, MIT, 1975.Google Scholar
  45. [45]
    R. Horaud and J.M. Brady. On the geometric interpretation of image contours. In Proc. Int. Conf. Comp. Vision, London, U.K., June 1987.Google Scholar
  46. [46]
    D.P. Huttenlocher and S. Ullman. Object recognition using alignment. In Proc. Int. Conf. Comp. Vision, pages 102–111, London, U.K., June 1987.Google Scholar
  47. [47]
    Y.L. Kergosien. La famille des projections orthogonales d’une surface et ses singularités. C.R. Acad. Sc. Paris, 292:929–932, 1981.MATHMathSciNetGoogle Scholar
  48. [48]
    B.B. Kimia, A.R. Tannenbaum, and S.W. Zucker. The shape triangle: parts, protrusions and bends. Technical Report TR-92-15, McGill University Research Center for Intelligent Machines, 1992.Google Scholar
  49. [49]
    B.B. Kimia, A.R. Tannenbaum, and S.W. Zucker. Shapes, shocks, and deformations I: the components of shape and the reaction-diffusion space. Int. J. of Comp. Vision, 15:189–224, 1995.CrossRefGoogle Scholar
  50. [50]
    J.J. Koenderink. What does the occluding contour tell us about solid shape? Perception, 13:321–330, 1984.CrossRefGoogle Scholar
  51. [51]
    J.J. Koenderink. Solid Shape. MIT Press, Cambridge, MA, 1990.Google Scholar
  52. [52]
    J.J. Koenderink and A.J. Van Doorn. The singularities of the visual mapping. Biological Cybernetics, 24:51–59, 1976.CrossRefMATHGoogle Scholar
  53. [53]
    J.J. Koenderink and A.J. Van Doorn. The internal representation of solid shape with respect to vision. Biological Cybernetics, 32:211–216, 1979.MATHCrossRefGoogle Scholar
  54. [54]
    J.J. Koenderink and A.J. Van Doorn. Representation of local geometry in the visual system. Biological Cybernetics, 55:367–375, 1987.MATHCrossRefMathSciNetGoogle Scholar
  55. [55]
    J.J. Koenderink and A.J. Van Doorn. Local features of smooth shapes: Ridges and courses. In Geometric Methods in Computer Vision II, pages 2–13, 1993.Google Scholar
  56. [56]
    D.J. Kriegman and J. Ponce. Computing exact aspect graphs of curved objects: solids of revolution. Int. J. of Comp. Vision, 5(2):119–135, 1990.CrossRefGoogle Scholar
  57. [57]
    D.J. Kriegman and J. Ponce. A new curve tracing algorithm and some applications. In P.J. Laurent, A. Le Méhauté, and L.L. Schumaker, editors, Curves and Surfaces, pages 267–270. Academic Press, New York, 1991.Google Scholar
  58. [58]
    M. Leyton. A process grammar for shape. Artificial Intelligence, 34:213–247, 1988.CrossRefGoogle Scholar
  59. [59]
    J. Liu, J.L. Mundy, D. Forsyth, A. Zisserman, and C. Rothwell. Efficient recognition of rotationally symmetric surfaces and straight homogeneous generalized cylinders. In Proc. IEEE Conf. Comp. Vision Patt. Recog., pages 123–128, New York City, NY, 1993.Google Scholar
  60. [60]
    C. Loop. Smooth spline surfaces over irregular meshes. Computer Graphics, pages 303–310, Aug. 1994.Google Scholar
  61. [61]
    W. Lorensen and H. Cline. Marching cubes: a high resolution 3D surface construction algorithm. Computer Graphics, 21:163–169, 1987.CrossRefGoogle Scholar
  62. [62]
    D. Lowe. The viewpoint consistency constraint. Int. J. of Comp. Vision, 1(1):57–72, 1987.CrossRefGoogle Scholar
  63. [63]
    D. Lowe and T.O. Binford. Segmentation and aggregation: An approach to figure-ground phenomena. In Proc. DARPA Image Understanding Workshop, pages 168–178, 1982.Google Scholar
  64. [64]
    A. Mackworth and F. Mokhtarian. The renormalized curvature scale space and the evolution properties of planar curves. In Proc. IEEE Conf. Comp. Vision Patt. Recog., pages 318–326, 1988.Google Scholar
  65. [65]
    D. Marr. Vision. Freeman, San Francisco, 1982.Google Scholar
  66. [66]
    D. Marr and K. Nishihara. Representation and recognition of the spatial organization of three-dimensional shapes. Proc. Royal Society, London, B-200:269–294, 1978.Google Scholar
  67. [67]
    A.P. Morgan. SolvingPol ynomial Systems using Conti nuation for Engineering and Scientific Problems. Prentice Hall, Englewood Cliffs, NJ, 1987.Google Scholar
  68. [68]
    Y. Moses and S. Ullman. Limitations of non model-based recognition schemes. In Proc. European Conf. Comp. Vision, pages 820–828, 1992.Google Scholar
  69. [69]
    J.L. Mundy and A. Zisserman. Geometric Invariance in Computer Vision. MIT Press, Cambridge, Mass., 1992.Google Scholar
  70. [70]
    J.L. Mundy, A. Zisserman, and D. Forsyth. Applications of Invariance in Computer Vision, volume 825 of Lecture Notes in Computer Science. Springer-Verlag, 1994.Google Scholar
  71. [71]
    H. Murase and S. Nayar. Visual learning and recognition of 3D objects from appearance. Int. J. of Comp. Vision, 14(1):5–24, 1995.CrossRefGoogle Scholar
  72. [72]
    V.S. Nalwa. Line-drawing interpretation: bilateral symmetry. In Proc. DARPA Image Understanding Workshop, pages 956–967, Los Angeles, CA, February 1987.Google Scholar
  73. [73]
    V.S. Nalwa. A guided tour of computer vision. Addison Wesley, 1993.Google Scholar
  74. [74]
    R. Nevatia and T.O. Binford. Description and recognition of complex curved objects. Artificial Intelligence, 8:77–98, 1977.MATHCrossRefGoogle Scholar
  75. [75]
    Quang-Loc Nguyen and M.D. Levine. Representing 3D objects in range images using geons. Computer Vision and Image Understanding, 63(1):158–168, January 1996.CrossRefGoogle Scholar
  76. [76]
    A. Noble, D. Wilson, and J. Ponce. On Computing Aspect Graphs of Smooth Shapes from Volumetric Data. Computer Vision and Image Understanding: special issue on Mathematical Methods in Biomedical Image Analysis, 66(2):179–192, 1997.Google Scholar
  77. [77]
    A.P. Pentland. Perceptual organization and the representation of natural form. Artificial Intelligence, 28:293–331, 1986.CrossRefMathSciNetGoogle Scholar
  78. [78]
    S. Petitjean. Géométrie énumérative et contacts de variétés linéaires: application aux graphes d’aspects d’objets courbes. PhD thesis, Institut National Polytechnique de Lorraine, 1995.Google Scholar
  79. [79]
    S. Petitjean, J. Ponce, and D.J. Kriegman. Computing exact aspect graphs of curved objects: Algebraic surfaces. Int. J. of Comp. Vision, 9(3):231–255, 1992.CrossRefGoogle Scholar
  80. [80]
    J. Ponce. On characterizing ribbons and finding skewed symmetries. Comp. Vis. Graph. Im. Proc., 52:328–340, 1990.CrossRefGoogle Scholar
  81. [81]
    J. Ponce. Straight homogeneous generalized cylinders: differential geometry and uniqueness results. Int. J. of Comp. Vision, 4(1):79–100, 1990.CrossRefMathSciNetGoogle Scholar
  82. [82]
    J. Ponce and J.M. Brady. Toward a surface primal sketch. In T. Kanade, editor, Three-dimensional machine vision, pages 195–240. Kluwer Publishers, 1987.Google Scholar
  83. [83]
    J. Ponce and D. Chelberg. Finding the limbs and cusps of generalized cylinders. Int. J. of Comp. Vision, 1(3):195–210, October 1987.CrossRefGoogle Scholar
  84. [84]
    J. Ponce, D. Chelberg, and W. Mann. Invariant properties of straight homogeneous generalized cylinders and their contours. IEEE Trans. Patt. Anal. Mach. Intell., 11(9):951–966, September 1989.CrossRefGoogle Scholar
  85. [85]
    W. Richards, J.J. Koenderink, and D.D. Hoffman. Inferring 3D shapes from 2D codons. MIT AI Memo 840, MIT Artificial Intelligence Lab, 1985.Google Scholar
  86. [86]
    M. Richetin, M. Dhome, J.T. Lapresté, and G. Rives. Inverse perspective transform from zero-curvature curve points: Application to the localization of some generalized cylinders from a single view. IEEE Trans. Patt. Anal. Mach. Intell., 13(2):185–191, February 1991.CrossRefGoogle Scholar
  87. [87]
    J.H. Rieger. On the classification of views of piecewise-smooth objects. Image and Vision Computing, 5:91–97, 1987.CrossRefGoogle Scholar
  88. [88]
    J.H. Rieger. Global bifurcations sets and stable projections of non-singular algebraic surfaces. Int. J. of Comp. Vision, 7(3):171–194, 1992.CrossRefGoogle Scholar
  89. [89]
    L.G. Roberts. Machine perception of three-dimensional solids. In J.T. Tippett et al., editor, Optical and Electro-Optical Information Processing, pages 159–197. MIT Press, Cambridge, 1965.Google Scholar
  90. [90]
    A. Rosenfeld. Axial representations of shape. Comp. Vis. Graph. Im. Proc., 33:156–173, 1986.CrossRefGoogle Scholar
  91. [91]
    R. Rothe. Darstellende Geometrie des Geländes. 1914.Google Scholar
  92. [92]
    De Saint-Venant. Surfaces à plus grande pente constituées sur des lignes courbes. Bulletin de la soc. philomath. de Paris, March 1852.Google Scholar
  93. [93]
    H. Sato and T.O. Binford. Finding and recovering SHGC objects in an edge image. CVGIP: Image Understanding, 57:346–358, 1993.CrossRefGoogle Scholar
  94. [94]
    C. Schmid and R. Mohr. Local grayvalue invariants for image retrieval. IEEE Trans. Patt. Anal. Mach. Intell., 19(5):530–535, May 1997.CrossRefGoogle Scholar
  95. [95]
    J. Serra. Image Analysis and Mathematical Morphology. Academic Press, New York, 1982.MATHGoogle Scholar
  96. [96]
    J.A. Sethian. Level set methods: evolvingi nterfaces in geometry, fluid mechanics, computer vision and materials sciences. Cambridge University Press, 1996.Google Scholar
  97. [97]
    S.A. Shafer. Shadows and Silhouettes in Computer Vision. Kluwer Academic Publishers, 1985.Google Scholar
  98. [98]
    S.A. Shafer and T. Kanade. The theory of straight homogeneous generalized cylinders and a taxonomy of generalized cylinders. Technical Report CMU-CS-83–105, Carnegie-Mellon University, 1983.Google Scholar
  99. [99]
    I. Shimshoni and J. Ponce. Finite-resolution aspect graphs of polyhedral objects. IEEE Trans. Patt. Anal. Mach. Intell., 19(4):315–327, 1997.CrossRefGoogle Scholar
  100. [100]
    L. Shirman and C. Sequin. Local surface interpolation with Bezier patches. CAGD, 4:279–295, 1987.MATHMathSciNetGoogle Scholar
  101. [101]
    K. Siddiqi and B.B. Kimia. Parts of visual form: computational aspects. IEEE Trans. Patt. Anal. Mach. Intell., 17(3):239–251, March 1995.CrossRefGoogle Scholar
  102. [102]
    D. Slater and G. Healey. Recognizing 3-d objects using local color invariants. IEEE Trans. Patt. Anal. Mach. Intell., 18(2):206–210, 1996.CrossRefGoogle Scholar
  103. [103]
    B.I Soroka and R. Bajcsy. Generalized cylinders from cross-sections. In Third Int. J. Conf. Patt. Recog., pages 734–735, 1976.Google Scholar
  104. [104]
    D. Stam. Distributed homotopy continuation and its application to robotic grasping. Master’s thesis, University of Illinois at Urbana-Champaign, 1992. Beckman Institute Tech. Report UIUC-BI-AI-RCV-92-03.Google Scholar
  105. [105]
    J. Stewman and K.W. Bowyer. Creating the perspective projection aspect graph of polyhedral objects. In Proc. Int. Conf. Comp. Vision, pages 495–500, Tampa, FL, 1988.Google Scholar
  106. [106]
    S. Sullivan and J. Ponce. Automatic model construction, pose estimation, and object recognition from photographs using triangular splines. In Proc. Int. Conf. Comp. Vision, pages 510–516, 1998.Google Scholar
  107. [107]
    S. Sullivan and J. Ponce. Automatic model construction, pose estimation, and object recognition from photographs using triangular splines. IEEE Trans. Patt. Anal. Mach. Intell., 20(10), Oct. 1998. In press.Google Scholar
  108. [108]
    S. Sullivan, L. Sandford, and J. Ponce. Using geometric distance fits for 3D object modelling and recognition. IEEE Trans. Patt. Anal. Mach. Intell., 16(12):1183–1196, December 1994.CrossRefGoogle Scholar
  109. [109]
    J.P. Thirion and G. Gourdon. The 3D marching lines algorithm: new results and proofs. Technical Report 1881-1, INRIA, 1993.Google Scholar
  110. [110]
    R.Y. Tsai. A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras. Journal of Robotics and Automation, RA-3(4):323–344, 1987.CrossRefGoogle Scholar
  111. [111]
    M. Turk and A.P. Pentland. Face recognition using eigenfaces. J. of Cognitive Neuroscience, 3(1), 1991.Google Scholar
  112. [112]
    S. Ullman and R. Basri. Recognition by linear combination of models. IEEE Trans. Patt. Anal. Mach. Intell., 13(10):992–1006, 1991.CrossRefGoogle Scholar
  113. [113]
    F. Ulupinar and R. Nevatia. Using symmetries for analysis of shape from contour. In Proc. Int. Conf. Comp. Vision, pages 414–426, Tampa, FL, December 1988.Google Scholar
  114. [114]
    C.E. Weatherburn. Differential geometry. Cambridge University Press, 1927.Google Scholar
  115. [115]
    I. Weiss. Projective invariants of shapes. In Proc. IEEE Conf. Comp. Vision Patt. Recog., pages 291–297, Ann Arbor, MI, 1988.Google Scholar
  116. [116]
    M. Wertheimer. Laws of organization in perceptual forms. Psychol. Forsch., 4:301–350, 1923. English translation in: W.B. Ellis, A source book of Gestalt psychology pages 71-88, 1973.Google Scholar
  117. [117]
    A.P. Witkin. Scale-space filtering. In Proc. International Joint Conference on Artificial Intelligence, pages 1019–1022, Karlsruhe, Germany, 1983.Google Scholar
  118. [118]
    M. Zerroug and G. Medioni. The challenge of generic object recongnition. In M. Hebert, J. Ponce, T.E. Boult, and A. Gross, editors, Object Representation for Computer Vision, number 994 in Lecture Notes in Computer Science, pages 217–232. Springer-Verlag, 1995.Google Scholar
  119. [119]
    M. Zerroug and R. Nevatia. Using invariance and quasi-invariance for the segmentation and recovery of curved objects. In J.L. Mundy, A. Zisserman, and D. Forsyth, editors, Applications of Invariance in Computer Vision, volume 825 of Lecture Notes in Computer Science, pages 317–340. Springer-Verlag, 1994.Google Scholar
  120. [120]
    A. Zisserman, D.A. Forsyth, J.L. Mundy, and C.A. Rothwell. Recognizing general curved objects efficiently. In J. Mundy and A. Zisserman, editors, Geometric Invariance in Computer Vision, pages 228–251. MIT Press, Cambridge, Mass., 1992.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Jean Ponce
    • 1
  • Martha Cepeda
    • 1
  • Sung-il Pae
    • 1
  • Steve Sullivan
    • 1
  1. 1.Dept. of Computer Science and Beckman InstituteUniversity of IllinoisUrbanaUSA

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