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. 2002 Sep 22;269(1503):1939–1947. doi: 10.1098/rspb.2002.2119

Recognizing novel three-dimensional objects by summing signals from parts and views.

David H Foster 1, Stuart J Gilson 1
PMCID: PMC1691113  PMID: 12350257

Abstract

Visually recognizing objects at different orientations and distances has been assumed to depend either on extracting from the retinal image a viewpoint-invariant, typically three-dimensional (3D) structure, such as object parts, or on mentally transforming two-dimensional (2D) views. To test how these processes might interact with each other, an experiment was performed in which observers discriminated images of novel, computer-generated, 3D objects, differing by rotations in 3D space and in the number of parts (in principle, a viewpoint-invariant, 'non-accidental' property) or in the curvature, length or angle of join of their parts (in principle, each a viewpoint-dependent, metric property), such that the discriminatory cue varied along a common physical scale. Although differences in the number of parts were more readily discriminated than differences in metric properties, they showed almost exactly the same orientation dependence. Overall, visual performance proved remarkably lawful: for both long (2 s) and short (100 ms) display durations, it could be summarized by a simple, compact equation with one term representing generalized viewpoint-invariant parts-based processing of 3D object structure, including metric structure, and another term representing structure-invariant processing of 2D views. Object discriminability was determined by summing signals from these two independent processes.

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Selected References

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  1. Atkinson J., Campbell F. W., Francis M. R. The magic number 4 +/- 0: a new look at visual numerosity judgements. Perception. 1976;5(3):327–334. doi: 10.1068/p050327. [DOI] [PubMed] [Google Scholar]
  2. Barlow H. B., Narasimhan R., Rosenfeld A. Visual pattern analysis in machines and animals. Science. 1972 Aug 18;177(4049):567–575. doi: 10.1126/science.177.4049.567. [DOI] [PubMed] [Google Scholar]
  3. Biederman I., Bar M. Differing views on views: response to Hayward and Tarr (2000). Vision Res. 2000;40(28):3901–3905. doi: 10.1016/s0042-6989(00)00180-2. [DOI] [PubMed] [Google Scholar]
  4. Biederman I., Bar M. One-shot viewpoint invariance in matching novel objects. Vision Res. 1999 Aug;39(17):2885–2899. doi: 10.1016/s0042-6989(98)00309-5. [DOI] [PubMed] [Google Scholar]
  5. Biederman I., Gerhardstein P. C. Recognizing depth-rotated objects: evidence and conditions for three-dimensional viewpoint invariance. J Exp Psychol Hum Percept Perform. 1993 Dec;19(6):1162–1182. doi: 10.1037//0096-1523.19.6.1162. [DOI] [PubMed] [Google Scholar]
  6. Biederman I. Recognition-by-components: a theory of human image understanding. Psychol Rev. 1987 Apr;94(2):115–147. doi: 10.1037/0033-295X.94.2.115. [DOI] [PubMed] [Google Scholar]
  7. Bülthoff H. H., Edelman S. Psychophysical support for a two-dimensional view interpolation theory of object recognition. Proc Natl Acad Sci U S A. 1992 Jan 1;89(1):60–64. doi: 10.1073/pnas.89.1.60. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Cutzu F., Edelman S. Representation of object similarity in human vision: psychophysics and a computational model. Vision Res. 1998 Aug;38(15-16):2229–2257. doi: 10.1016/s0042-6989(97)00186-7. [DOI] [PubMed] [Google Scholar]
  9. Durlach N. I., Braida L. D. Intensity perception. I. Preliminary theory of intensity resolution. J Acoust Soc Am. 1969 Aug;46(2):372–383. doi: 10.1121/1.1911699. [DOI] [PubMed] [Google Scholar]
  10. Edelman S., Intrator N. (Coarse coding of shape fragments) + (retinotopy) approximately = representation of structure. Spat Vis. 2000;13(2-3):255–264. doi: 10.1163/156856800741072. [DOI] [PubMed] [Google Scholar]
  11. Foster D. H. A spatial perturbation technique for the investigation of discrete internal representations of visual patterns. Biol Cybern. 1980;38(3):159–169. doi: 10.1007/BF00337405. [DOI] [PubMed] [Google Scholar]
  12. Foster D. H. An approach to the analysis of the underlying structure of visual space using a generalized notion of visual pattern recognition. Biol Cybern. 1975;17(2):77–79. doi: 10.1007/BF00363947. [DOI] [PubMed] [Google Scholar]
  13. Foster D. H., Ferraro M. Visual gap and offset discrimination and its relation to categorical identification in brief line-element displays. J Exp Psychol Hum Percept Perform. 1989 Nov;15(4):771–784. doi: 10.1037//0096-1523.15.4.771. [DOI] [PubMed] [Google Scholar]
  14. Foster D. H., Kahn J. I. Internal representations and operations in the visual comparison of transformed patterns: effects of pattern point-inversion, position symmetry, and separation. Biol Cybern. 1985;51(5):305–312. doi: 10.1007/BF00336917. [DOI] [PubMed] [Google Scholar]
  15. Foster D. H., Mason R. J. Transformation and relational-structure schemes for visual pattern recognition. Two models tested experimentally with rotated random-dot patterns. Biol Cybern. 1979 Mar 6;32(2):85–93. doi: 10.1007/BF00337439. [DOI] [PubMed] [Google Scholar]
  16. Foster D. H., Simmons D. R., Cook M. J. The cue for contour-curvature discrimination. Vision Res. 1993 Feb;33(3):329–341. doi: 10.1016/0042-6989(93)90089-f. [DOI] [PubMed] [Google Scholar]
  17. Foster D. H. Visual comparison of random-dot patterns: evidence concerning a fixed visual association between features and feature-relations. Q J Exp Psychol. 1978 Nov;30(4):637–654. doi: 10.1080/14640747808400690. [DOI] [PubMed] [Google Scholar]
  18. Hayward W. G., Tarr M. J. Differing views on views: comments on Biederman and Bar (1999). Vision Res. 2000;40(28):3895–3899. doi: 10.1016/s0042-6989(00)00179-6. [DOI] [PubMed] [Google Scholar]
  19. Hayward W. G., Williams P. Viewpoint dependence and object discriminability. Psychol Sci. 2000 Jan;11(1):7–12. doi: 10.1111/1467-9280.00207. [DOI] [PubMed] [Google Scholar]
  20. Hoffman D. D., Richards W. A. Parts of recognition. Cognition. 1984 Dec;18(1-3):65–96. doi: 10.1016/0010-0277(84)90022-2. [DOI] [PubMed] [Google Scholar]
  21. Hummel J. E., Stankiewicz B. J. Categorical relations in shape perception. Spat Vis. 1996;10(3):201–236. doi: 10.1163/156856896x00141. [DOI] [PubMed] [Google Scholar]
  22. Ishai A., Ungerleider L. G., Martin A., Schouten J. L., Haxby J. V. Distributed representation of objects in the human ventral visual pathway. Proc Natl Acad Sci U S A. 1999 Aug 3;96(16):9379–9384. doi: 10.1073/pnas.96.16.9379. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Lawson R., Humphreys G. W. View specificity in object processing: evidence from picture matching. J Exp Psychol Hum Percept Perform. 1996 Apr;22(2):395–416. doi: 10.1037//0096-1523.22.2.395. [DOI] [PubMed] [Google Scholar]
  24. Logothetis N. K., Sheinberg D. L. Visual object recognition. Annu Rev Neurosci. 1996;19:577–621. doi: 10.1146/annurev.ne.19.030196.003045. [DOI] [PubMed] [Google Scholar]
  25. Luck S. J., Vogel E. K. The capacity of visual working memory for features and conjunctions. Nature. 1997 Nov 20;390(6657):279–281. doi: 10.1038/36846. [DOI] [PubMed] [Google Scholar]
  26. Marr D., Nishihara H. K. Representation and recognition of the spatial organization of three-dimensional shapes. Proc R Soc Lond B Biol Sci. 1978 Feb 23;200(1140):269–294. doi: 10.1098/rspb.1978.0020. [DOI] [PubMed] [Google Scholar]
  27. Rouder J. N. Assessing the roles of change discrimination and luminance integration: evidence for a hybrid race model of perceptual decision making in luminance discrimination. J Exp Psychol Hum Percept Perform. 2000 Feb;26(1):359–378. [PubMed] [Google Scholar]
  28. Shepard R. N., Metzler J. Mental rotation of three-dimensional objects. Science. 1971 Feb 19;171(3972):701–703. doi: 10.1126/science.171.3972.701. [DOI] [PubMed] [Google Scholar]
  29. Sutherland N. S. Outlines of a theory of visual pattern recognition in animals and man. Proc R Soc Lond B Biol Sci. 1968 Dec 31;171(1024):297–317. doi: 10.1098/rspb.1968.0072. [DOI] [PubMed] [Google Scholar]
  30. Tarr M. J., Bülthoff H. H. Image-based object recognition in man, monkey and machine. Cognition. 1998 Jul;67(1-2):1–20. doi: 10.1016/s0010-0277(98)00026-2. [DOI] [PubMed] [Google Scholar]
  31. Tarr M. J., Bülthoff H. H. Is human object recognition better described by geon structural descriptions or by multiple views? Comment on Biederman and Gerhardstein (1993). J Exp Psychol Hum Percept Perform. 1995 Dec;21(6):1494–1505. doi: 10.1037//0096-1523.21.6.1494. [DOI] [PubMed] [Google Scholar]
  32. Tarr M. J., Kriegman D. J. What defines a view? Vision Res. 2001 Jul;41(15):1981–2004. doi: 10.1016/s0042-6989(01)00024-4. [DOI] [PubMed] [Google Scholar]
  33. Tarr M. J., Williams P., Hayward W. G., Gauthier I. Three-dimensional object recognition is viewpoint dependent. Nat Neurosci. 1998 Aug;1(4):275–277. doi: 10.1038/1089. [DOI] [PubMed] [Google Scholar]
  34. Ullman S. Aligning pictorial descriptions: an approach to object recognition. Cognition. 1989 Aug;32(3):193–254. doi: 10.1016/0010-0277(89)90036-x. [DOI] [PubMed] [Google Scholar]
  35. Vanrie J., Willems B., Wagemans J. Multiple routes to object matching from different viewpoints: mental rotation versus invariant features. Perception. 2001;30(9):1047–1056. doi: 10.1068/p3200. [DOI] [PubMed] [Google Scholar]
  36. Willems B., Wagemans J. Matching multicomponent objects from different viewpoints: mental rotation as normalization? J Exp Psychol Hum Percept Perform. 2001 Oct;27(5):1090–1115. doi: 10.1037//0096-1523.27.5.1090. [DOI] [PubMed] [Google Scholar]

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