Similarity-based models of human visual recognition

Vision Research

Volumn 38, Issue 15-16, 1998, Pages 2289-2305

  Unzicker, A ^a   Juttner M ^a   Rentschler, I ^a  

^a UNIVERSITY OF MUNICH   (Germany)

Author keywords

Classification; Modeling; Recognition; Supervised learning

Indexed keywords

ADULT; ARTICLE; CLASSIFICATION; COGNITION; FEMALE; HUMAN; MALE; MODEL; NORMAL HUMAN; PATTERN RECOGNITION; PRIORITY JOURNAL; PRODUCTIVITY; PSYCHOPHYSICS; RECOGNITION; SIGNAL DETECTION; VISUAL MEMORY;

COGNITION; FOVEA CENTRALIS; HUMANS; LEARNING; LIKELIHOOD FUNCTIONS; MATHEMATICS; MODELS, PSYCHOLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, VISUAL; PSYCHOPHYSICS;

EID: 0345676499     PISSN: 00426989     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0042-6989(97)00396-9     Document Type: Article

References (75)

1. Watanabe S Pattern Recognition. 1985;Wiley, New York.
2. Duda RO, Hart PE Pattern Classification and Scene Analysis. 1973;Wiley, New York.
3. Ahmed N, Rao K Orthogonal Transforms for Digital Signal Processing. 1975;Springer, New York.
4. Pratt WK Digital Image Processing. 1978;Wiley, New York.
5. Sklansky J, Wassel GN Pattern Classifiers and Trainable Machines. 1981;Springer, New York.
6. Dudai Y The Neurobiology of Memory. 1989;Oxford University Press, Oxford.
7. Koriat A, Norman J Mental rotation and visual familiarity. Percept Psychophys. 37:1985;429-439.
8. Rock I, DiVita J A case of viewer-cantered object perception. Cogn Psychol. 19:1987;280-283.
9. Edelman S, Poggio T Bringing the grandmother back into the picture: A memory-based view of object recognition. Int J Pattern Recogn. 6:1992;37.
10. Edelman S, Bülthoff H Orientation dependence in the recognition of familiar and novel views of three-dimensional objects. Vis Res. 32(12):1992;2385-2400.
11. Caelli T, Rentschler I, Scheidler W Visual pattern recognition in humans. I. Evidence for adaptive filtering. Biol Cybern. 57:1987;233-240.
12. Rentschler I, Jüttner M, Caelli T Probabilistic analysis of human supervised learning and classification. Vis Res. 34:1994;669-687.
13. Jüttner M, Rentschler I Reduced perceptual dimensionality in extrafoveal vision. Vis Res. 36(7):1996;1007-1022.
14. Mumford D Mathematical Theories of Shape. Proc SPIE 1570 Geometric Methods in Computer Vision. 1991;2-10.
15. Tversky A Features of similarity. Psychol Rev. 84:1977;327-352.
16. Rentschler I, Treutwein B Loss of spatial phase relationships in extrafoveal vision. Nature. 313:1985;308-310.
17. Rentschler I, Caelli T Detection and recognition. Haken H, Stadler M Synergetics of Cognition. 1990;233-248 Springer, New York.
18. Rentschler I, Barth E, Caelli T, Zetsche C, Jüttner M Generalization of form in visual pattern classification. Spatial Vis. 10:1996;59-85.
19. Edelman S Representation, similarity, and the chorus of prototypes. Minds Mach. 5:1995;15-46.
20. Shepard RN The analysis of proximities: Multidimensional scaling with an unknown distance function. I. Psychometrika. 27:1962;125-140.
21. Shepard RN The analysis of proximities: Multidimensional scaling with an unknown distance function. II. Psychometrika. 27:1962;219-246.
22. Caelli T, Bischof W Machine learning paradigms for pattern recognition and image understanding. Spatial Vis. 10:1996;87-103.
23. Cutzu F, Edelman S Faithful representation of similarities among three-dimensional shapes in human vision. Proc Natl Acad Sci. 93:1996;12046-12050.
24. Thurstone LL Psychological analysis. Am J Psychol. 38:1927;368-389.
25. Green DM, Swets JA Signal Detection Theory and Pschophysics. 1974;Krieger, New York.
26. Reed SK Pattern recognition and categorization. Cogn Psychol. 3:1972;346-382.
27. Ashby FG Multidimensional Models of Perception and Cognition. 1992;Erlbaum, Hillsdale.
28. Reed SK Pschological Processes in Pattern Recognition. 1973;Academic Press, New York.
29. Brooks L Nonanalytic concept formation and memory for instances. Rosch E, Loyd B Cognition and Categorization. 1978;Erlbaum, Hillsdale.
30. Estes W Array models for category learning. Cogn Psychol. 18:1986;500-549.
31. Medin D, Schaffer M Context theory of classification learning. Psychol Rev. 85:1978;207-238.
32. Nosofsky RM Attention, similarity, and the identification categorization relationship. J Exp Psychol General. 115:1986;39-57.
33. Ashby FG, Perrin NA Toward a unified theory of similarity recognition. Psychol Rev. 95:1988;124-150.
34. Ashby FG, Gott J Decision rules in the perception and categorization of multidimensional stimuli. J Exp Psychol Learning Mem Cogn. 14:1988;33-53.
35. Gauss C. Teoria motus. English translation (1963): Theory of the motion of the heavenly bodies about the sun in conic sections. New York: Dover, 1809.
36. Gelb A Applied Optimal Estimation. 1974;MIT Press, Cambridge, MA.
37. Rentschler I, Jüttner M, Caelli T Ideal observers for supervised learning and classification. Steyer R, Wender K, Widaman K Psychometric Methodology. 1993;2554-2558 Fischer, Stuttgart: Gustav.
38. Poggio T, Girosi F Regularization algorithms for learning that are equivalent to multilayer networks. Science. 247(4945):1990;978.
39. Poggio T, Fahle M, Edelman S Fast perceptual learning in visual hyperacuity. Science. 256:1992;1018-1021.
40. Maruyama M, Teraoka T, Abe S Recognition of 3D flexible objects by GRBF. Biol Cybern. 70:1994;377-385.
41. Logothetis N, Pauls J, Bülthoff H, Poggio T View-dependent object recognition by monkeys. Curr Biol. 4(5):1994;401-413.
42. Jain R, Binford T Dialogue-Ignorance, myopia, and naivety in computer vision systems. CVGIP: Image Understand. 53:1991;112-117.
43. Snyder MA Reply. A commentary on the paper by Jain and Binford. CVGIP: Image Understand. 53:1991;118-119.
44. Robson J Receptive fields: neural representation of the spatial and intensity attributes of the visual image. Carterette E, Friedman MP Handbook of Perception. 1975;81-116 Academic Press, New York.
45. Pollen DA, Ronner SF Phase relations between adjacent simple cells in the visual cortex. Science. 212:1981;1409-1411.
46. Burr DC, Morrone MC, Spinelli D Evidence for edge and bar detectors in human vision. Vis Res. 29:1989;419-431.
47. Zeevi YY, Porat M Image representation by localized phase. Proc SPIE 1199: Vis Commun Image Process. 1989;1512-1517.
48. Wegmann B, Zetzsche C. Visual system based polar quantization of local amplitude and local phase of orientation filter outputs. In: Human Vision and Electronic Imaging: Models, Methods, and Applications. Proc SPIE 1249, 1990, pp. 607-613.
49. Nazir TA, O'Regan JK Some results on translation invariance in the human visual system. Spatial Vis. 5:1990;1-19.
50. Rovamo J, Virsu V An estimation and application of the human cortical magnification factor. Exp Brain Res. 37:1979;495-510.
51. Nosofsky RM Choice, similarity, and the context theory of classification. J Exp Psychol Learning Mem Cogn. 10:1984;104-114.
52. Luce RD Detection and recognition. Luce RD, Bush RR, Galanter E Handbook of Mathematical Psychology. 1963;103-189 Wiley, New York.
53. Kahana M, Bennett PJ Classification and perceived similarity of compound gratings that differ in relative spatial phase. Percept Psychophys. 55(6):1994;642-656.
54. Gray R Vector quantization. IEEE Mag. 4:1984;4-28.
55. Unzicker A, Jüttner M, Rentschler I. Modeling the dynamics of visual classification learning. Math Soc Sci, 1998 (to appear).
56. Shepard RN Toward a universal law of generalization for psychological science. Science. 237:1987;1317-1323.
57. Nosofsky RM, Smith J Similarity, identification, and categorization: comment on Ashby and Lee, 1990. J Exp Psychol General. 121(2):1991;237-245.
58. Ashby FG, Maddox WT Integrating information from separable psychological dimensions. J Exp Psychol Hum Percept Perform. 16:1990;598-612.
59. Ashby FG, Maddox WT Complex decision rules in categorization: Contrasting novice and experienced performance. J Exp Psychol Hum Percept Perform. 18:1992;50-71.
60. Nasrabadi NM, King RA Image coding using vector quantization: a review. IEEE Trans Commun. 36:1988;957-971.
61. Hertz J, Krogh A, Palmer G Introduction to the Theory of Neural Computing. 1990;Addison-Wesley, Reading, MA.
62. Hecht-Nielsen R Counterpropagation networks. Appl Opt. 26:1987;4979-4984.
63. Huang WY, Lippman RP Neural net and traditional classifiers. Anderson DZ Neural Information Processing Systems. 1988;387-396 American Institute of Physics, New York.
64. Specht DF Probabilistic neural networks. Neural Networks. 3:1990;109-118.
65. Poggio T, Edelman S A network that learns to recognize three-dimensional objects. Nature. 343(6255):1990;263.
66. Bülthoff H, Edelman S Evaluating object recognition theories by computer graphics psychophysics. Glaser D, Poggio T Exploring Brain Functions: Models in Neuroscience. 1992;Wiley, New York.
67. Nelder J, Mead R A simplex method for function minimization. Comput J. 7:1965;308-313.
68. Borg I, Lingoes J Multidimensional Similarity Structure Analysis. 1987;Springer, New York.
69. Cohen M, Massaro D On the similarity of categorization models. Ashby FG Multidimensional Models of Perception and Cognition. 1992;395-447 Erlbaum, New York.
70. Dill M, Wolf R, Heisenberg M Visual pattern recognition in Drosophila involves retinotopic matching. Nature. 365:1993;751-753.
71. Virsu V, Rovamo J, Nasanen R Cortical magnification factor predicts the photopic contrast sensitivity of peripheral vision. Nature. 271:1978;54-56.
72. Strasburger H, Rentschler I, Harvey L Cortical magnification theory fails to predict visual recognition. Eur J Neurosci. 6:1994;1583-1588.
73. Azzopardi P, Cowey A The overrepresentation of the fovea and adjacent retina in the striate cortex and the dorsal lateral geniculate nucleus of the macaque monkey. Neuroscience. 72:1996;627-639.
74. Jüttner M, Caelli T, Reutschles I Recognition-by-parts: a computational approach to human learning and generalization of shapes. Biol Cyber. 74:1996;521-535.
75. Cover TM, Wagner TJ Topics in statistical pattern recognition. Fu KS Digital Pattern Recognition. 1976;15-46 Springer, New York.