Perceptual segmentation and the perceived orientation of dot clusters: The role of robust statistics

Journal of Vision

Volumn 8, Issue 7, 2008, Pages

  Cohen, Elias H ^a,b   Singh, Manish ^a   Maloney, Laurence T ^c  

^a RUTGERS UNIVERSITY   (United States)

^b STATE UNIVERSITY OF NEW YORK   (United States)

^c NEW YORK UNIVERSITY   (United States)

Author keywords

Orientation perception; Perceptual grouping; Principal axis; Probabilistic segmentation; Robust statistics

Indexed keywords

ARTICLE; COMPARATIVE STUDY; HUMAN; ORIENTATION; PATTERN RECOGNITION; PHOTOSTIMULATION; PHYSIOLOGY; STATISTICAL MODEL;

FORM PERCEPTION; HUMANS; MODELS, STATISTICAL; ORIENTATION; PHOTIC STIMULATION;

EID: 44349169541     PISSN: None     EISSN: 15347362     Source Type: Journal    
DOI: 10.1167/8.7.6     Document Type: Article

References (51)

1. Biederman, I. (1987). Recognition-by-components: A theory of human image understanding. Psychological Review, 94, 115-147.
2. Blum, H. (1973). Biological shape and visual science: I. Journal of Theoretical Biology, 38, 205-287.
3. Blum, H., & Nagel, R. N. (1978). Shape description using weighted symmetric axis features. Pattern Recognition, 10, 167-180.
4. Bracewell, R. N. (2000). The Fourier transformation and its applications (3rd ed.). New York: McGraw-Hill.
5. Brady, M., & Asada, H. (1984). Smoothed local symmetries and their implementation. International Journal of Robotics Research, 3, 36-61.
6. Burbeck, C. A., & Zauberman, G. S. (1997). Across-object relationships in perceived object orientation. Vision Research, 37, 879-884.
7. Cohen, E. H., Schnitzer, B. S., Gersch, T. M., Singh, M., & Kowler, E. (2007). The relationship between spatial pooling and attention in saccadic and perceptual tasks. Vision Research, 47, 1907-1923.
8. Cohen, E. H., & Singh, M. (2006). Perceived orientation of complex shape reflects graded part decomposition. Journal of Vision, 6(8):4, 805-821, http://journalofvision.org/6/8/4/, doi:10.1167/ 6.8.4.
9. Denisova, K., Singh, M., & Kowler, E. (2006). The role of part structure in the perceptual localization of a shape. Perception, 35, 1073-1087.
10. De Winter, J., & Wagemans, J. (2006). Segmentation of object outlines into parts: A large scale integrative study. Cognition, 99, 275-325.
11. Driver, J., & Baylis, G. C. (1996). Edge assignment and figure-ground segmentation in visual short-term matching. Cognitive Psychology, 31, 248-306.
12. Elder, J. H., & Goldberg, R. M. (2002). Ecological statistics of Gestalt laws for the perceptual organization of contours. Journal of Vision, 2(4):5, 324-353, http://journalofvision.org/2/4/5/, doi:10.1167/2.4.5.
13. Feldman, J. (1997). Curvilinearity, covariance, and regularity in perceptual groups. Vision Research, 37, 2835-2848.
14. Feldman, J. (2001). Bayesian contour integration. Perception & Psychophysics, 63, 1171-1182.
15. Feldman, J., & Singh, M. (2006). Bayesian estimation of the shape skeleton. Proceedings of the National Academy of Sciences of the United States of America, 103, 18014-18019.
16. Geisler, W. S., Perry, J. S., Super, B. J., & Gallogly, D. P. (2001). Edge co-occurrence in natural images predicts contour grouping performance. Vision Research, 41, 711-724.
17. Hampel, F. R. (1974). The influence curve and its role in robust estimation. Journal of the American Statistical Association, 69, 383-393.
18. Hoffman, D. D., & Richards, W. A. (1984). Parts of recognition. Cognition, 18, 65-96.
19. Hoffman, D. D., & Singh, M. (1997). Salience of visual parts. Cognition, 63, 29-78.
20. Hon, A., Maloney, L. T., & Landy, M. S. (1997). The influence function for visual interpolation. SPIE Proceedings Series, 3016, 409-419.
21. Huber, P. J. (1981). Robust statistics. New York: Wiley-Interscience. Jurečková, J., & Pickek, J. (2005). Robust statistical methods in R. New York: Chapman & Hall.
22. Knill, D. C., & Richards, W. (1996). Perception as Bayesian inference. Cambridge, UK: Cambridge University Press.
23. Koffka, K. (1935). Principles of Gestalt Psychology. New York: Harcourt Brace.
24. Kubovy, M., & Wagemans, J. (1995). Grouping by proximity and multistability in dot lattices: A quantitative gestalt theory. Psychological Science, 6, 225-234.
25. Landy, M. S., Maloney, L. T., Johnston, E., & Young, M. (1995). Measurement and modeling of depth cue combination: In defense of weak fusion. Vision Research, 35, 389-412.
26. Lánský, P., Yakimoff, N., & Radil, T. (1987). On visual orientation of dot patterns. Biological Cybernetics, 56, 389-396.
27. Lánský, P., Yakimoff, N., Radil, T., & Mitrani, L. (1989). Errors in estimating the orientation of dot patterns. Perception, 18, 237-242.
28. Lehman, E. L. (1983). Theory of point estimation. New York: Wiley.
29. Leyton, M. (1987). Symmetry-curvature duality. Computer Vision, Graphics, and Image Processing, 38, 327-341.
30. Li, W., & Westheimer, G. (1997). Human discrimination of the implicit orientation of simple symmetrical patterns. Vision Research, 37, 565-572.
31. Liu, B., Dijkstra, T. M., & Oomes, A. H. (2002). The beholder's share in the perception of orientation of 2-D shapes. Perception & Psychophysics, 64, 1227-1247.
32. Maronna, R. D., Martin, R. A., & Yohai, V. J. (2006). Robust statistics, theory and methods. Chichester, UK: Wiley.
33. Marr, D., & Nishihara, H. K. (1978). Representation and recognition of three-dimensional shapes. Proceedings of the Royal Society of London B: Biological Sciences, 200, 269-294.
34. Melcher, D., & Kowler, E. (1999). Shape, surfaces and saccades. Vision Research, 39, 2929-2946.
35. McDermott, J., & Adelson, E. H. (2004). The geometry of the occluding contour and its effect on motion interpretation. Journal of Vision, 4(10):9, 944-954, http://journalofvision.org/4/10/9/, doi:10.1167/ 4.10.9.
36. McDermott, J., Weiss, Y., & Adelson, E. H. (2001). Beyond junctions: Nonlocal form constraints on motion interpretation. Perception, 30, 905-923.
37. Obrecht, N., Chapman, G. B., & Gelman, R, (2007). Intuitive t tests: Lay use of statistical information. Psychonomic Bulletin & Review, 14, 1147-1152.
38. Oomes, A. H., & Dijkstra, T. M. (2002). Object pose: Perceiving 3-D shape as sticks and slabs. Perception & Psychophysics, 64, 507-520.
39. Peterson, M., & Gibson, B. (1994). Must figure-ground perception precede object recognition? An assumption in peril. Psychological Science, 5, 253-259.
40. Rock, I., & Brosgole, L. (1964). Grouping based on phenomenal proximity. Journal of Experimental Psychology, 67, 531-538.
41. Rubin, E. (1958). Figure and ground. In D. C. Beardslee & M. Wertheimer (Eds.), Readings in perception (pp. 194-203). Princeton, NJ: Van Nostrand. (Original work published 1915).
42. Singh, M., & Fulvio, J. M. (2005). Visual extrapolation of contour geometry. Proceedings of the National Academy of Sciences of the United States of America, 102, 939-944.
43. Singh, M., & Hoffman, D. (2001). Part-based representations of visual shape and implications for visual cognition. In T. Shipley & P. Kellman (Eds.), From fragments to objects: Grouping and segmentation in vision. Advances in psychology series (vol. 130, pp. 401-459). New York: Elsevier Science.
44. Tukey, J. W. (1960). A survey of sampling from contaminated distributions. In I. Olkin (Ed.), Contributions to probability and statistics (pp. 448-485). Stanford University Press.
45. Vishwanath, D., Kowler, E., & Feldman, J. (2000). Saccadic localization of occluded targets. Vision Research, 40, 2797-2811.
46. Warren, P. A., Maloney, L. T., & Landy, M. S. (2002). Interpolating sampled contours in 3-D: Analyses of variability and bias. Vision Research, 42, 2431-2446.
47. Warren, P. A., Maloney, L. T., & Landy, M. S. (2004). Interpolating sampled contours in 3D: Perturbation analyses. Vision Research, 44, 815-832.
48. Wertheimer, M. (1923). Laws of organization in perceptual forms. Psychologische Forschung, 4, 301-350.
49. Yakimoff, N. (1981). Does assignment of orientation to dot patterns reveal optimization processes in the visual system? Biological Cybernetics, 42, 39-43.
50. Yodogawa, E. (1985). Quantitative measure of perceived orientation strength of dot patterns. Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 584-588.
51. Zhu, S. C. (1999). Embedding Gestalt laws in Markov random fields. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21, 1170-1187.