The representation of three-dimensional object similarity in human vision

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 3016, Issue , 1997, Pages 460-471

  Cutzu, Florin ^a   Tarr, Michael J ^a  

^a BROWN UNIVERSITY   (United States)

Author keywords

Natural categories; Shape classification; Silhouettes; Similarity

Indexed keywords

IMAGE CLASSIFICATION; THREE DIMENSIONAL;

HUMAN VISION; NATURAL CATEGORIES; SHAPE CLASSIFICATION; SILHOUETTES; SIMILARITY; VISION PROBLEMS; VISUAL TASKS;

GAIT ANALYSIS;

EID: 0347069154     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.274544     Document Type: Conference Paper

References (52)

1. P. Jolicoeur and G. K. Humphrey, "Perception of rotated two-dimensional and three-dimensional objects and visual shapes," in Perceptual constancies, V. Walsh and J. Kulikowski, eds., ch. 10, Cambridge University Press, Cambridge, UK, 1996. in press.
2. I. Biederman, "Recognition by components: a theory of human image understanding," Psychol. Review 94, pp. 115-147, 1987.
3. I. Biederman and P. C. Gerhardstein, "Recognizing depth-rotated objects: Evidence and conditions for three-dimensional viewpoint invariance," Journal of Experimental Psychology: Human Perception and Performance 19(6), pp. 1162-1182, 1993.
4. H. H. Bülthoff and S. Edelman, "Psychophysical support for a 2-D view interpolation theory of object recognition," Proceedings of the National Academy of Science 89, pp. 60-64, 1992.
5. G. K. Humphrey and S. C. Khan, "Recognizing novel views of three-dimensional objects," Canadian Journal of Psychology 46, pp. 170-190, 1992.
6. F. Cutzu and S. Edelman, "Canonical views in object representation and recognition," Vision Research 34, pp. 3037-3056, 1994.
7. H. H. Bülthoff, S. Edelman, and M. J. Tarr, "How are three-dimensional objects represented in the brain?," Cerebral Cortex 5, pp. 247-260, 1995.
8. M. J. Tarr, "Rotating objects to recognize them: A case study of the role of viewpoint dependency in the recognition of three-dimensional objects," Psychonomic Bulletin and Review 2(1), pp. 55-82, 1995.
9. S. Edelman and D. Weinshall, "Computational approaches to shape constancy," in Perceptual constancies: why things look as they do, V. Walsh and J. Kulikowski, eds., Cambridge University Press, Cambridge, UK, 1996. in press.
10. S. Ullman, High level vision, MIT Press, Cambridge, MA, 1996.
11. D. Marr and H. K. Nishihara, "Representation and recognition of the spatial organization of three dimensional structure," Proceedings of the Royal Society of London B 200, pp. 269-294, 1978.
12. T. Poggio and S. Edelman, "A network that learns to recognize three-dimensional objects," Nature 343, pp. 263-266, 1990.
13. S. Ullman and R. Basri, "Recognition by linear combinations of models," IEEE Transactions on Pattern Analysis and Machine Intelligence 13, pp. 992-1005, 1991.
14. S. Edelman, "Representation of similarity in 3D object discrimination," Neural Computation 7, pp. 407-422, 1995.
15. R. Ellis, D. A. Allport, G. W. Humphreys, and J. Collis, "Varieties of object constancy," Q. Journal Exp. Psychol. 41A, pp. 775-796, 1989.
16. E. Rosch, C. B. Mervis, W. D. Gray, D. M. Johnson, and P. Boyes-Braem, "Basic objects in natural categories," Cognitive Psychology 8, pp. 382-439, 1976.
17. B. Tversky and K. Hemenway, "Objects, parts, and categories," Journal of Experimental Psychology: General 113, pp. 169-193, 1984.
18. W. Torgerson, Theory and Methods of Scaling, John Wiley & Sons, Inc., New York, 1958.
19. R. N. Shepard, "Representation of structure in similarity data: Problems and prospects," Psychometrika 39, pp. 373-421, 1974.
20. R. N. Shepard, "Multidimensional scaling, tree-fitting, and clustering," Science 210, pp. 390-397, 1980.
21. R. M. Nosofsky, "Exemplar-based approach to relating categorization, idenitification, and recognition," in Multidimensional models of perception and cognition, F. G. Ashby, ed., pp. 363-394, Lawrence Erlbaum, Hilisdale, NJ, 1992.
22. R. M. Nosofsky, "Similarity scaling and cognitive process models," arp 43, pp. 25-53, 1992.
23. F. G. Ashby, "Multidimensional models of categorization," in Multidimensional models of perception and cognition, F. G. Ashby, ed., pp. 449-484, Lawrence Erlbaum, Hillsdale, NJ, 1992.
24. N. A. Perrin, "Uniting identification, similarity and preference: general recognition theory," in Multidimensional models of perception and cognition, F. G. Ashby, ed., pp. 123-146, Lawrence Erlbaum, Hillsdale, NJ, 1992.
25. D. M. Green and J. A. Swets, Signal detection theory and psychophysics, Wiley, New York, 1966.
26. A. Tversky, "Features of similarity," Psychological Review 84, pp. 327-352, 1977.
27. R. Beals, D. H. Krantz, and A. Tversky, "The foundations of multidimensional scaling," Psychological Review 75, pp. 127-142, 1968.
28. R. M. Nosofsky, "Overall similarity and the identification of separable-dimension stimuli: a choice model analysis," Perception and Psychophysics 38, pp. 415-432, 1985.
29. R. M. Nosofsky, "Tests of an exemplar model for relating perceptual classification and recognition memory," Journal of Experimental Psychology: Human Perception and Performance 17, pp. 3-27, 1991.
30. W. T. Maddox and F. G. Ashby, "Comparing decision bound and exemplar models of categorization," Perception and Psychophysics 53, pp. 49-70, 1993.
31. Y. Moses, S. Ullman, and S. Edelman, "Generalization to novel images in upright and inverted faces," Perception 25, pp. 443-462, 1996.
32. W. G. Hayward, "Effects of outline shape in object recognition," Journal of Experimental Psychology: Human Perception and Performance in press, 1997.
33. W. G. Hayward and M. J. Tarr, "Testing conditions for viewpoint invariance in object recognition," Journal of Experimental Psychology: Human Perception and Performance in press, 1997.
34. C. T. Zahn and R. Z. Roskies, "Fourier descriptors for plane closed curves," IEEE Transactions on Computers C-21, pp. 269-81, March 1972.
35. E. Persoon and K. Fu, "Shape discrimination using fourier descriptors," IEEE Transactions on Pattern Analysis and Machine Intelligence 8, pp. 388-397, May 1986.
36. K. Arbter, W. Snyder, H. Burkhardt, and G. Hirzinger, "Application of affine-invariant fourier descriptors to recognition of 3-d objects," IEEE Transactions on Pattern Analysis and Machine Intelligence 12, pp. 640-647, July 1990.
37. G. H. Granlund, "Fourier processing for hand print character recognition," IEEE Transactions on Computers C-21, pp. 195-201, February 1972.
38. R. N. Shepard and G. W. Cermak, "Perceptual-cognitive explorations of a toroidal set of free-form stimuli," Cognitive Psychology 4, pp. 351-377, 1973.
39. J. M. Cortese and B. P. Dyre, "Perceptual similarity of shapes generated from Fourier Descriptors," Journal of Experimental Psychology: Human Perception and Performance 22, pp. 133-143, 1996.
40. M. A. Kurbat, E. E. Smith, and D. L. Medin, "Categorization, typicality, and shape similarity," in Proceedings of the Sixteenth Anual Conference of the Cognitive Science Society, Lawrence Erlbaum, (Hillsdale, NJ), 1994.
41. M. Werman and D. Weinshall, "Similarity and affine invariant distance between point sets," IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-17(8), pp. 810-814, 1995.
42. I. Borg and J. Lingoes, Multidimensional Similarity Structure Analysis, Springer, Berlin, 1987.
43. P. C. Quinn, P. D. Eimas, and S. L. Rosenkrantz, "Evidence for representations of perceptually similar natural categories by 3-month-old and 4-month-old infants," Perception 22, pp. 463-475, 1993.
44. F. Cutzu and S. Edelman, "Faithful representation of similarities among three-dimensional shapes in human vision," Proceedings of the National Academy of Science 93, pp. 12046-12050, 1996.
45. S. Palmer, E. Rosch, and P. Chase, "Canonical perspective and the perception of objects," in Attention and Performance IX, J. Long and A. Baddeley, eds., pp. 135-151, Lawrence Erlbaum, Hillsdale, NJ, 1981.
46. V. Blanz, M. J. Tarr, H. H. Bülthoff, and T. Vetter, "What object attributes determine canonical views?," Tech. Rep. 42, Max-Planck Institute for Biological Cybernetics, 1996.
47. R. M. Nosofsky, "Exemplar-based accounts of relations between classification, recognition, and typicality," Journal of Experimental Psychology: Learning, Memory and Cognition 14, pp. 700-708, 1988.
48. D. Weinshall, M. Werman, and N. Tishby, "Stability and likelihood of views of three dimensional objects," in Proc. 10th Israeli Symposium on Computer Vision and AI, R. Basri, U. Schild, and Y. Stein, eds., pp. 445-454, 1993.
49. J. E. Hummel and I. Biederman, "Dynamic binding in a neural network for shape recognition," Psychological Review 99(3), pp. 480-517, 1992.
50. M. J. Tarr and S. Pinker, "When does human object recognition use a viewer-centered reference frame?," Psychological Science 1(42), pp. 253-256, 1990.
51. S. Edelman, "Class similarity and viewpoint invariance in the recognition of 3D objects," Biological Cybernetics 72, pp. 207-220, 1995.
52. M. J. Tarr and H. H. Bülthoff, "Is human object recognition better described by geon-structural-descriptions or by multiple-views?," Journal of Experimental Psychology: Human Perception and Performance 21(6), pp. 1494-1505, 1995.