The structure of perceptual categories

Journal of Mathematical Psychology

Volumn 41, Issue 2, 1997, Pages 145-170

  Feldman, Jacob ^a  

^a RUTGERS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0031167914     PISSN: 00222496     EISSN: None     Source Type: Journal    
DOI: 10.1006/jmps.1997.1154     Document Type: Article

References (58)

1. Aitkin M., Rubin D. Estimation and hypothesis testing in finite mixture models. Journal of the Royal Statistical Society B. 47:1985;67-75.
2. Ashby F. G. Multidimensional models of categorization. Multidimensional models of perception and cognition. 1992;Lawrence Erlbaum, Hillsdale.
3. Ashby F. G., Perrin N. A. Toward a unified theory of similarity and recognition. Psychology Review. 95:1988;124-150.
4. Barlow H. Unsupervised learning. Neural Computation. 1:1989;295-311.
5. Barr A. Global and local deformations of solid primitives. Computer Graphics. 28:1984;21-30.
6. Barrow H. G., Tenenbaum J. M. Interpreting line drawings as three-dimensional surfaces. Artificial Intelligence. 17:1981;75-116.
7. Bennett B. M., Hoffman D. D., Prakash C. Observer mechanics: A formal theory of perception. 1989;Academic Press, London.
8. Binford T. Inferring surfaces from images. Artificial Intelligence. 17:1981;205-244.
9. Bobick A. Technical Report. 1001:1987.
10. Davey B., Priestley H. Introduction to lattices and order. 1990;Cambridge University Press, Cambridge.
11. Everitt B., Hand D. Finite mixture distributions. 1981;Chapman and Hall, London.
12. Farouki R., Hinds J. A hierarchy of geometric forms. IEEE Computer Graphics and Applications. 1985;51-78.
13. Feldman J. Proceedings of the 13th Annual Conference of the Cognitive Science Society. 1991.
14. Feldman J. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1992a.
15. J. Feldman, 1992b, Perceptual categories and world regularities, Massachusetts Institute of Technology.
16. Feldman J. Perceptual models of small dot clusters. Proceedings of the DIMACS Workshop on Partitioning Data Sets. DIMACS Series in Discrete Mathematics and Theoretical Computer Science. 19:1995;. p. 331-355.
17. Feldman J. Regularity vs genericity in the perception of collinearity. Perception. 25:1996;335-342.
18. Fodor J. Concepts: a potboiler. Cognition. 50:1994;95-113.
19. Fried L. S., Holyoak K. J. Induction of category distributions: A framework for classification learning. Journal of Experimental Psychology: Learning, Memory, and Cognition. 10:1984;234-257.
20. J. Ghosh, P. Sen, 1985, On the asymptotic performance of the log likelihood ratio statistic for the mixture model and related results, L. Le CamR. Olshen, Proceedings of the Berkeley Conference in the Honor of Jersy Neyman and Jack Kieffer, 2.
21. Hatfield G., Epstein W. The status of the minimum principle in the theoretical analysis of visual perception. Psychological Bulletin. 97:1985;155-186.
22. Hochberg J., McAlister E. A quantitative approach to figural "goodness. Journal of Experimental Psychology. 46:1953;361-364.
23. Hoel P., Port S., Stone C. Introduction to statistical theory. 1971;Houghton Mifflin, Boston.
24. Jepson A., Richards W. A. What is a percept? Occasional Paper. 43:1991;MIT Center for Cognitive Science.
25. Jepson A., Richards W. A. A lattice framework for integrating vision modules. IEEE Transactions on Systems, Man, and Cybernetics. 22:1992;1087-1096.
26. Jepson A., Richards W. A. What makes a good feature. Harris L., Jenkin M. Spatial Vision in Humans and Robots. 1992;Cambridge University Press.
27. Kanade T. Recovery of the three-dimensional shape of an object from a single view. Artificial Intelligence. 17:1981;409-460.
28. Landau B., Jackendoff R. "What" and "where" in spatial language and spatial cognition. Behavioral and Brain Sciences. 16:1993;217-265.
29. Leeuwenberg E. A perceptual coding language for visual and auditory patterns. American Journal of Psychology. 84:1971;307-349.
30. Leeuwenberg E., Boselie F. Against the likelihood principle in visual form perception. Psychological Review. 95:1988;485-491.
31. Leyton M. Perceptual organization as nested control. Biological Cybernetics. 51:1984;141-153.
32. Leyton M. A process-grammar for shape. Artificial Intelligence. 34:1988;213-247.
33. Leyton M. Inferring causal history from shape. Cognitive Science. 13:1989;357-387.
34. Leyton M. Symmetry, Causality, Mind. 1992;M.I.T. Press, Cambridge.
35. Lowe D. G. Three-dimensional object recognition from single two-dimensional images. Artificial Intelligence. 31:1987;355-395.
36. Mark L., Shapiro B., Shaw R. Structural support for the perception of growth. Journal of Experimental Psychology: Human Perception and Performance. 1986;149-159.
37. McLachlan G., Basford K. Mixture models: Inference and applications to clustering. 1988;Marcel Dekker, New York.
38. Poston T., Stewart I. N. Catastrophe theory and its applications. 1978;Pitman Publishing Limited, London.
39. Quine W. On simple theories of a complex world. Foster M., Martin M. Probability, confirmation, and simplicity: Readings in the philosophy of inductive logic. 1965;Odyssey Press, New York.
40. Quine W. Natural kinds. Kornblith H. Naturalizing Epistemology. 1985;M.I.T. Press, Cambridge.
41. Quinn B., McLachlan G., Hjort N. A note on the Aitkin-Rubin approach to hypothesis testing in mixture models. Journal of the Royal Statistical Society B. 49:1987;311-314.
42. Richards W. A., Bobick A. Playing twenty questions with nature. Pylyshyn Z. Computational Processes in Human Vision: An Interdisciplinary Perspective. 1988;3-26 Ablex Publishing Corporation, Norwood.
43. Richards W. A., Feldman J., Jepson A. Proceedings of the British machine vision conference. 1992.
44. Richards W. A., Jepson A., Feldman J. Priors, preferences, and categorical percepts. Knill D., Richards W. A. Perception as Bayesian Inference. 1996;Cambridge University Press, Cambridge.
45. Rissanen J. Modeling by shortest data description. Automatica. 14:1978;465-471.
46. Rosch E., Mervis C., Gray W., Johnson D., Boyes-Braem P. Basic objects in natural categories. Cognitive Psychology. 8:1976;382-439.
47. E. Saund, 1987, Dimensionality-reduction using connectionist networks, Massachusetts Institute of Technology Artificial Intelligence Laboratory.
48. Shepard R. Toward a universal law of generalization for psychological science. Science. 237:1987;1317-1323.
49. Silverman B. W. Density estimation for statistics and data analysis. 1986;Chapman and Hall, London.
50. Simon H. Complexity and the representation of patterned sequences of symbols. Psychological Review. 79:1972;369-382.
51. Smith E., Medin D. Categories and Concepts. 1981;Harvard University Press, Cambridge.
52. Sober E. Simplicity. 1975;Oxford University Press, London.
53. Thompson D. On growth and form. 1942;Cambridge University Press, Cambridge.
54. Watanabe S. Knowing and guessing: a quantitative study of inference and information. 1969;John Wiley, New York.
55. Watanabe S. Pattern recognition: human and mechanical. 1985;John Wiley, New York.
56. Weyl H. Symmetry. 1952;Princeton University Press, Princeton.
57. Witkin A. P., Tenenbaum J. M. On the role of structure in vision. Beck J., Hope B., Rosenfeld A. Human and machine vision. 1983;481-543 Academic Press, San Diego.
58. Zucker S. W., Davis S. Points and endpoints: a size/spacking constraint for dot grouping. Perception. 17:1988;229-247.