OSA's Digital Library

Journal of the Optical Society of America A

Journal of the Optical Society of America A

| OPTICS, IMAGE SCIENCE, AND VISION

  • Vol. 18, Iss. 9 — Sep. 1, 2001
  • pp: 2331–2370

Three-systems theory of human visual motion perception: review and update

Zhong-Lin Lu and George Sperling  »View Author Affiliations


JOSA A, Vol. 18, Issue 9, pp. 2331-2370 (2001)
http://dx.doi.org/10.1364/JOSAA.18.002331


View Full Text Article

Acrobat PDF (3064 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

Lu and Sperling [Vision Res. <b>35</b>, 2697 (1995)] proposed that human visual motion perception is served by three separate motion systems: a first-order system that responds to moving luminance patterns, a second-order system that responds to moving modulations of feature types—stimuli in which the expected luminance is the same everywhere but an area of higher contrast or of flicker moves, and a third-order system that computes the motion of marked locations in a “salience map,” that is, a neural representation of visual space in which the locations of important visual features (“figure”) are marked and “ground” is unmarked. Subsequently, there have been some strongly confirmatory reports: different gain-control mechanisms for first- and second-order motion, selective impairment of first- versus second- and/or third-order motion by different brain injuries, and the classification of new third-order motions, e.g., isoluminant chromatic motion. Various procedures have successfully discriminated between second- and third-order motion (when first-order motion is excluded): dual tasks, second-order reversed phi, motion competition, and selective adaptation. Meanwhile, eight apparent contradictions to the three-systems theory have been proposed. A review and reanalysis here of the new evidence, pro and con, resolves the challenges and yields a more clearly defined and significantly strengthened theory.

© 2001 Optical Society of America

OCIS Codes
(330.4150) Vision, color, and visual optics : Motion detection

Citation
Zhong-Lin Lu and George Sperling, "Three-systems theory of human visual motion perception: review and update," J. Opt. Soc. Am. A 18, 2331-2370 (2001)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-18-9-2331


Sort:  Author  |  Year  |  Journal  |  Reset

References

  1. E. G. Boring, Sensation and Perception in the History of Experimental Psychology: A History of Experimental Psychology, 2nd ed. (Appleton-Century-Crofts, New York, 1942).
  2. F. Kenkel, “Untersuchungen ueber Zusammenhang zwischen Erscheinungsgross und Erscheinungsbewegung beim einigen sogenannten optischen Tauschungen,” Z. Psychol. 61, 358–449 (1913).
  3. A. Korte, “Kinematoskopische Untersuchungen,” Z. Psychol. 72, 193–206 (1915).
  4. M. Wertheimer, “Ueber das Sehen von Scheinbewegunen und Scheinkorpern,” Z. Psychol. 61, 161–265 (1912).
  5. O. Braddick, “A short-range process in apparent motion,” Vision Res. 14, 519–529 (1974).
  6. A. Pantle and L. Picciano, “A multistable movement display: evidence for two separate motion systems in human vision,” Science 193, 500–502 (1976).
  7. G. Mather, P. Cavanagh, and A. M. Anstis, “A moving display which opposes short-range and long-range signals,” Perception 14, 163–166 (1985).
  8. M. A. Georgeson and T. M. Shackleton, “Monocular motion sensing, binocular motion perception,” Vision Res. 29, 1511–1523 (1989).
  9. P. Cavanagh and G. Mather, “Motion: the long and the short of it,” Spatial Vision 4, 103–129 (1989).
  10. P. Cavanagh, “Short-range vs long-range motion: not a valid distinction,” Spatial Vision 5, 303–309 (1991).
  11. C. Chubb and G. Sperling, “Two motion perception mechanisms revealed by distance driven reversal of apparent motion,” Proc. Natl. Acad. Sci. USA 86, 2985–2989 (1989).
  12. W. Reichardt, “Autokorrelationsauswertung als funktionsprinzip des zentralnervensystems,” Z. Naturforsch. 12b, 447–457 (1957).
  13. W. Reichardt, “Autocorrelation, a principle for the evaluation of sensory information by the central nervous system,” in Sensory Communication, W. A. Rosenblith, ed. (Wiley, New York, 1961).
  14. J. P. H. van Santen and G. Sperling, “Temporal covariance model of human motion perception,” J. Opt. Soc. Am. A 1, 451–473 (1984).
  15. J. P. H. van Santen and G. Sperling, “Elaborated Reichardt detectors,” J. Opt. Soc. Am. A 2, 300–321 (1985).
  16. E. H. Adelson and J. R. Bergen, “Spatio-temporal energy models for the perception of apparent motion,” J. Opt. Soc. Am. A 2, 284–299 (1985).
  17. E. H. Adelson and J. R. Bergen, “The extraction of spatio-temporal energy in human and machine vision,” in Motion: Representation and Analysis (IEEE Workshop Proceedings), (IEEE Computer Society Press, Washington D.C., 1986) pp. 151–155.
  18. D. Marr and S. Ullman, “Directional selectivity and its use in early visual processing,” Proc. R. Soc. London Ser. B 211, 151–180 (1981).
  19. C. L. Fennema and W. B. Thompson, “Velocity determination in scenes containing several moving objects,” Comput. Graph. 9, 301–315 (1979).
  20. A. Johnston, P. W. McOwan, and H. Buxton, “A computational model of the analysis of some first-order and second-order motion patterns by simple and complex cells,” Proc. R. Soc. London Ser. B 250, 297–306 (1992).
  21. B. Hassenstein and W. Reichardt, “Systemtheoretische analyse der zeit-, reihenfolgen- and vorzeichenauswertung bei der bewegungsperzeption des russelkafers chlorophanus,” Z. Naturforsch. 11b, 513–524 (1956).
  22. A. B. Watson and A. J. Ahumada, Jr., “A look at motion in the frequency domain,” in Motion: Perception and Representation, J. K. Tsotsos, ed. (Association for Computing Machinery, New York, 1983) pp. 1–10.
  23. D. J. Heeger, “A model for the extraction of image flow,” J. Opt. Soc. Am. A 4, 1455–1471 (1987).
  24. H. R. Wilson, V. P. Ferrera, and C. Yo, “A psychophysically motivated model for two-dimensional motion perception,” Visual Neurosci. 9, 79–97 (1992).
  25. S. J. Nowlan and T. J. Sejnowski, “Filter selection model for motion segmentation and velocity integration,” J. Opt. Soc. Am. A 11, 3177–3200 (1994).
  26. V. S. Ramachandran, M. V. Rau, and T. R. Vidyasagar, “Apparent movement with subjective contours,” Vision Res. 13, 1399–1401 (1973).
  27. G. Sperling, “Movement perception in computer-driven visual displays,” Behav. Res. Methods Instrum. 8, 144–151 (1976).
  28. A. M. M. Lelkens and J. J. Koenderink, “Illusory motion in visual displays,” Vision Res. 24, 293–300 (1984).
  29. A. M. Derrington and D. R. Badcock, “Separate detectors for simple and complex grating patterns?” Vision Res. 25, 1869–1878 (1985).
  30. C. Chubb and G. Sperling, “Drift-balanced random stimuli: a general basis for studying non-Fourier motion perception,” J. Opt. Soc. Am. A 5, 1986–2006 (1988).
  31. K. Turano and A. Pantle, “On the mechanism that encodes the movement of contrast variations—I: velocity discrimination,” Vision Res. 29, 207–221 (1989).
  32. J. D. Victor and M. M. Conte, “Motion mechanisms have only limited access to form information,” Vision Res. 30, 289–301 (1989).
  33. C. Chubb and G. Sperling, “Texture quilts: basic tools for studying motion-from-texture,” J. Math. Psychol. 35, 411–442 (1991).
  34. G. Sperling, “Visual form and motion perception: psychophysics, computation, and neural networks,” presented at Fourier and Non-Fourier Perception of Motion and Orientation, meeting dedicated to the memory of the late Kvetoslav Prazdny, Boston University, Boston, Mass., March 5, 1988.
  35. B. Julesz and R. Payne, “Difference between monocular and binocular stroboscopic motion perception,” Vision Res. 8, 433–444 (1968).
  36. J. T. Petersik, K. I. Hicks, and A. J. Pantle, “Apparent movement of successively generated subjective figures,” Perception 7, 371–383 (1978).
  37. M. Shadlen and T. Carney, “Mechanism of human motion revealed by new cyclopean illusion,” Science 232, 95–97 (1986).
  38. P. Cavanagh, M. Arguin, and M. von Grunau, “Interattribute apparent motion,” Vision Res. 29, 1379–1386 (1989).
  39. J. M. Zanker, “Theta motion: a paradoxical stimulus to explore higher order motion extraction,” Vision Res. 33, 553–569 (1993).
  40. Z.-L. Lu and G. Sperling, “Attention-generated apparent motion,” Nature 377, 237–239 (1995).
  41. Z.-L. Lu and G. Sperling, “The functional architecture of human visual motion perception,” Vision Res. 35, 2697–2722 (1995).
  42. R. Patterson, “Stereoscopic (cyclopean) motion sensing,” Vision Res. 39, 3329–3345 (1999).
  43. Z.-L. Lu and G. Sperling, “Three systems for visual motion perception,” Curr. Dir. Psychol. Sci. 5, 44–53 (1996).
  44. G. Sperling and Z.-L. Lu, “A systems analysis of human visual motion perception,” in High-Level Motion Processing, T. Watanabe, ed. (MIT Press, Cambridge, Mass., 1998), pp. 153–183.
  45. W. C. Shipley, F. A. Kenney, and M. E. King, “Beta apparent movement under binocular, monocular and interocular stimulation,” Am. J. Psychol. 58, 545–549 (1945).
  46. O. Braddick, “Low-level and high-level processes in apparent motion,” Philos. Trans. R. Soc. London, Ser. B 290, 137–151 (1980).
  47. Y.-X. Zhou and C. L. B. Baker, Jr, “A processing stream in mammalian visual cortex neurons for non-Fourier responses,” Science 261, 98–101 (1993).
  48. T. D. Albright, “Form-cue invariant motion processing in primate visual cortex,” Science 255, 1141–1143 (1992).
  49. T. Ledgeway and A. T. Smith, “Evidence for separate motion-detecting mechanisms for first- and second-order motion in human vision,” Vision Res. 34, 2727–2740 (1994).
  50. Y.-X. Zhou and C. L. Baker, Jr, “Spatial properties of envelope-responsive cells in area 17 and 18 neurons of the cat,” J. Neurophysiol. 75, 1038–1050 (1996).
  51. M. W. Greenlee and A. T. Smith, “Detection and discrimination of first- and second-order motion in patients with unilateral brain damage,” J. Neurosci. 17, 804–818 (1997).
  52. S. Nishida, T. Ledgeway, and M. D. Edwards, “Multiple-scale processing for motion in the human visual system,” Vision Res. 37, 2685–2698 (1997).
  53. C. E. Ho, “Letter recognition reveals pathways of second-order and third-order motion,” Proc. Natl. Acad. Sci. USA 95, 400–404 (1998).
  54. L. P. O’Keefe and J. A. Movshon, “Processing of first- and second-order motion signals by neurons in area MT of the macaque monkey,” Visual Neurosci. 15, 305–317 (1998).
  55. A. T. Smith, M. W. Greenlee, K. D. Singh, F. M. Kraemer, and J. Hennig, “The processing of first- and second-order motion in human visual cortex assessed by functional magnetic resonance imaging (fMRI),” J. Neurosci. 18, 3816–3830 (1998).
  56. E. Blaser, G. Sperling, and Z.-L. Lu, “Measuring the amplification and the spatial resolution of visual attention,” Proc. Natl. Acad. Sci. USA 96, 11681–11686 (1999).
  57. C. E. Ho and G. Sperling, “Selecting second and third-order motion pathways,” Invest. Ophthalmol. Visual Sci. ARVO Suppl. 40, S425 (1999).
  58. Z.-L. Lu, L. Lesmes, and G. Sperling, “Mechanisms of isoluminant chromatic motion perception,” Proc. Natl. Acad. Sci. USA 96, 8289–8294 (1999).
  59. Z.-L. Lu, L. Lesmes, and G. Sperling, “Perceptual motion standstill from rapidly moving chromatic displays,” Proc. Natl. Acad. Sci. USA 96, 15374–15379 (1999).
  60. I. Mareschal and C. L. Baker, Jr., “Cortical processing of second-order motion,” Visual Neurosci. 16, 1–14 (1999).
  61. N. E. Scott-Samuel and M. A. Georgeson, “Does early non-linearity account for second-order motion?” Vision Res. 39, 2853–2865 (1999).
  62. J. A. Solomon and M. J. Morgan, “Dichoptically canceled motion,” Vision Res. 39, 2293–2297 (1999).
  63. S. Nishida and H. Ashida, “A hierarchical structure of motion system revealed by interocular transfer of flicker motion aftereffects,” Vision Res. 40, 265–278 (2000).
  64. A. J. Schofield and M. A. Georgeson, “The temporal properties of first- and second-order vision,” Vision Res. 40, 2475–2487 (2000).
  65. G. Sperling, T.-S. Kim, and Z.-L. Lu, “Direction-reversal VEP’s reveal signature of first-and second-order motion,” Invest. Ophthalmol. Visual Sci. ARVO Suppl. 41, S334 (2000).
  66. G. Sperling and C. E. Ho, “Third-order versus first-order and second-order motion in ambiguous stimuli: competition reveals temporal tuning functions, monocularity/binocularity, and the role of attention,” Perception 29, 83 (2000).
  67. E. Taub, J. D. Victor, and M. M. Conte, “Nonlinear preprocessing in short-range motion,” Vision Res. 37, 1459–1477 (1997).
  68. N. M. Grzywacz, S. N. J. Watamaniuk, and S. P. McKee, “Temporal coherence theory for the detection and measurement of visual motion,” Vision Res. 35, 3183–3203 (1995).
  69. A. E. Seiffert and P. Cavanagh, “Position displacement, not velocity, is the cue to motion detection of second-order stimuli,” Vision Res. 38, 3569–3582 (1998).
  70. T. Carney, “Evidence for an early motion system which integrates information from the two eyes,” Vision Res. 37, 2361–2368 (1997).
  71. L. Zemany, C. F. Stromeyer III, A. Chaparro, and R. E. Kronauer, “Motion detection on stationary, flashed pedestal gratings: evidence for an opponent-motion mechanism,” Vision Res. 38, 795–812 (1998).
  72. A. T. Smith and T. Ledgeway, “Separate detection of moving luminance and contrast modulations: fact or artifact?” Vision Res. 37, 45–62 (1997).
  73. J. A. Solomon and G. Sperling, “Full-wave and half-wave rectification in 2nd-order motion perception,” Vision Res. 34, 2239–2257 (1994).
  74. C. Koch and S. Ullman, “Shifts in selective visual attention: towards the underlying neural circuitry,” Hum. Neurobiol. 4, 219–227 (1985).
  75. P. Burt, “Attention mechanisms for vision in a dynamic world,” in Proceedings of the Ninth International Conference on Pattern Recognition, Rome, Italy (IEEE Computer Society Press, Washington, D.C., 1988), pp. 977–987.
  76. M. Mozer, The Perception of Multiple Objects: a Connectionist Approach, (MIT Press, Cambridge, Mass., 1991).
  77. S. Ahmad and S. Omohundro, “Efficient visual search: a connectionist solution,” International Computer Science Institute Technical Report tr-91–040 (University of California, Berkeley, Calif., 1991).
  78. J. K. Tsotsos, S. M. Culhane, W. Y. K. Wai, Y. Lai, N. Davis, and F. Nuflo, “Modeling visual attention via selective tuning,” Artif. Intell. 78, 507–545 (1995).
  79. G. Sperling, A. Reeves, E. Blaser, Z.-L. Lu, and E. Weichselgartner, “Two computational models of attention,” in Attention, C. Koch and J. Braun, eds. (MIT Press, Cambridge, Mass., 2001), pp. 177–214.
  80. P. Werkhoven, G. Sperling, and C. Chubb, “Motion perception between dissimilar gratings: a single channel theory,” Vision Res. 33, 463–485 (1993).
  81. G. Sperling and Z. L. Lu, “Update on the three-motion-systems theory,” Invest. Ophthalmol. Visual Sci. ARVO Suppl. 39, S461 (1998).
  82. In actual practice, because the response of the early stages of visual processing before motion detection is a linear function of—i.e., faithfully represents—the dark–light difference only when the difference is less than approximately 5%, 83 84 the light bars must be no more than 2.5% lighter than the mean luminance and the dark bars no more than 2.5% darker than the mean luminance.
  83. K. Nakayama and G. H. Silverman, “Detection and discrimination of sinusoidal grating displacements,” J. Opt. Soc. Am. A 2, 267–274 (1985).
  84. Z.-L. Lu and G. Sperling, “Contrast gain control in first- and second-order motion perception,” J. Opt. Soc. Am. A 13, 2305–2318 (1996).
  85. W. Prinzmetal, H. Amiri, K. Allen, and T. Edwards, “Phenomenology of attention: I. Color, location, orientation, and spatial frequency,” J. Exp. Psychol. Hum. Percep. Perform. 24, 261–282 (1998).
  86. C. Tseng, J. L. Gobell, and G. Sperling, “Sensitization to color: induced by search, measured by motion,” Invest. Ophthalmol. Visual Sci. ARVO Suppl. 41, S40, Abstr nr. 207 (2000).
  87. S. M. Anstis, “Phi movement as a subtraction process,” Vision Res. 10, 1411–1430 (1970).
  88. S. M. Anstis and B. J. Rogers, “Illusory reversal of visual depth and movement during changes of contrast,” Vision Res. 15, 957–961 (1975).
  89. Second-order reversed phi was first reported by S. Nishida, “Spatiotemporal properties of motion perception for random-check contrast modulations,” Vision Res. 33, 633–645 (1993).
  90. Z.-L. Lu and G. Sperling, “Second-order reversed phi,” Percept. Psychophys. 61, 1075–1088 (1999).
  91. S. J. Anderson, D. C. Burr, and M. C. Morrone, “Two-dimensional spatial and spatial-frequency selectivity of motion-sensitive mechanisms in human vision,” J. Opt. Soc. Am. A 8, 1340–1351 (1991).
  92. Z.-L. Lu, G. Sperling, and J. Beck, “Selective adaptation of three motion systems,” Invest. Ophthalmol. Visual Sci. ARVO Suppl. 38, 237 (1997).
  93. L. M. Vaina, N. Makris, D. Kennedy, and A. Cowey, “The selective impairment of the perception of first-order motion by unilateral cortical brain damage,” Visual Neurosci. 15, 333–348 (1998).
  94. G. T. Plant, K. D. Laxer, N. M. Barbaro, J. S. Schiffman, and K. Nakayama, “Impaired visual motion perception in the contralateral hemifield following unilateral posterior cerebral lesions,” Brain 116, 1337–1353 (1993).
  95. L. M. Vaina, M. Le May, and N. M. Grzywacz, “Deficits of non-Fourier motion perception in a patient with normal performance on short-range motion tasks,” Soc. Neurosci. Abstract 19, 1284 (1993).
  96. L. M. Vaina and A. Cowey, “Impairment of the perception of second order motion but not first order motion in a patient with unilateral focal brain damage,” Proc. R. Soc. London Ser. B 263, 1225–1232 (1996).
  97. J. Rademacher, A. M. Galaburda, D. N. Kennedy, P. A. Pilipek, and V. S. Caviness, “Human cerebral cortex: localization, parcellation, and morphometry with magnetic resonance imaging,” J. Cog. Neurosci. 4, 352–374 (1992).
  98. L. M. Vaina, A. Cowey, and D. Kennedy, “Perception of first- and second-order motion: separable neurological mechanisms?” Hum. Brain Mapping 7, 67–77 (1999).
  99. C. L. Baker, Jr., “Central neural mechanisms for detecting second-order motion,” Curr. Opin. Neurobiol. 9, 461–466 (1999).
  100. C. Chubb and G. Sperling, “Second-order motion perception: space–time separable mechanisms,” in Proceedings: Workshop on Visual Motion (IEEE Computer Society Press, Washington, D.C., 1989), pp. 126–138.
  101. For a class of motion models consisting of a pointwise transformation T[f(x, y)] of the contrast of the input stimulus followed by a Reichardt (or equivalent motion energy) computation, this set of stimuli could potentially be used to provide the coefficients of a Taylor series expansion T[⋅]=fK (x, y), (K=1, ..., ∞) of an early pointwise nonlinearity, and thereby to exactly define the nonlinearity if fK (x, y) (K=1, 2, 3, or 4) activates only the Kth term in the Taylor series expansion of T. This scheme is awkward because, generally, the TVC higher-order stimuli activate more than one term in T. This is probably why Taub et el.67 discarded the Taylor expansion approach. On the other hand, the different terms in the Taylor expansion generate different spatial and temporal frequencies, and this could have been used to isolate and define T.
  102. Taub et el.67 use the term “motion amount” instead of the usual “motion energy” to indicate that motion is computed between pairs of points in immediately consecutive images in the stimulus, rather than, more commonly, between nearby or overlapping regions in space–time. To be consistent with the TVC model, TVC’s definition of MS TVC is used throughout this section.
  103. The TVC motion strength computation is not exactly a Reichardt computation, because the forward motion and the reverse motion are computed between different pairs of points rather than the same pairs of points, as in a Reichardt computation. However, because motion between all pairs of points is summed in the computations under consideration here, this subtle difference is insignificant. Further, the Taub et el.67 motion computation [Eq. (3)] is a pixel-by-pixel computation; all averaging occurs in summing all the pixel-by-pixel motions. A more realistic model would incorporate some averaging (spatial filtering) before each nonlinearity (intensity compression and motion-direction extraction). Our explorations with their model showed that such enhancements, while desirable, do not fundamentally change the character of the predictions. Jonathan D. Victor, Department of Neurology and Neuroscience, Cornell University Medical College, 1300 York Avenue, New York, N.Y. 10021 (personal communication, July 31, 1996).
  104. A. Johnston and C. W. G. Clifford, “A unified account of three apparent motion illusions,” Vision Res. 35, 1109–1123 (1995).
  105. A. Johnston and C. W. G. Clifford, “Perceived motion of contrast-modulated gratings: predictions of the multi-channel gradient model and the role of full-wave rectification,” Vision Res. 35, 1771–1783 (1995).
  106. A. Johnston, C. P. Benton, and P. W. McOwan, “Induced motion at texture-defined motion boundaries,” Proc. R. Soc. London Ser. B 266, 2441–2450 (1999).
  107. K. Nakayama and C. W. Tyler, “Psychophysical isolation of movement sensitivity by removal of familiar position cues,” Vision Res. 21, 427–433 (1981).
  108. D. H. Kelly, “Motion and vision: II. Stabilized spatio-temporal threshold surface,” J. Opt. Soc. Am. 69, 1340–1349 (1979).
  109. S. J. Anderson and D. C. Burr, “Spatial and temporal selectivity of the human motion detection system,” Vision Res. 25, 1147–1154 (1985).
  110. G. Sperling, H.-J. Kim, and Z.-L. Lu. (2001). “Is there interocular first-order motion?” Talk at annual meeting of the Association for Research in Vision and Ophthalmology, Fort Lauderdale, Fla., May 2, 2001.
  111. Why did these observers in the interocular motion experiment overlook the first-order perceptual wind when they had previously very successfully reported the motion of the wind in pedestaled luminance-modulation motion and pedestaled texture-contrast motion?41 Probably because of the context of the other trials. In pedestaled motion experiments, half of the stimuli have a pedestal, so observers are alerted to look for wind motion. In the interocular motion experiment, there was no pedestal. Most of the stimuli consist of a clearly moving grating. Only at the highest frequencies is there an illusory pedestal (which is created by motion standstill in the third-order system).59 In this context, the observers attempted to interpret the output of the third-order motion system, and they overlooked the first-order wind.
  112. H. J. Kim, Z.-L. Lu, and G. Sperling, “Rivalry motion versus depth motion,” Invest. Ophthalmol. Visual Sci. ARVO Suppl. 42, S736 (2001).
  113. C. Tseng, H. Kim, J. L. Gobell, Z.-L. Lu, and G. Sperling, “Motion standstill in rapidly moving stereoptic depth displays,” Invest. Ophthalmol. Visual Sci. ARVO Suppl. 42, S504, Abstract nr. 2720 (2001).
  114. Zemany et el.’s71 use of 28 frames was stimulated by a misstatement by Lu and Sperling41 : “... preserving pseudo-linearity requires exactly one full cycle plus one extra frame...” This is correct only for four-frame cycles. See the more general formulation in the text below.
  115. B. A. Dosher, M. S. Landy, and G. Sperling, “Kinetic depth effect and optic flow: 1. 3D shape from Fourier motion,” Vision Res. 29, 1789–1813 (1989).
  116. The MathWorks, Natick, Mass., 1997.
  117. A. T. Smith and T. Ledgeway, “Sensitivity to second-order motion as a function of temporal frequency and eccentricity,” Vision Res. 38, 403–410 (1998).
  118. Stimuli were created with HIPS image-processing software119 120 and displayed by using a software package (Runtime Library for Psychology Experiments, 1988) designed to drive an AT-Vista video graphics adapter installed in an IBM 486 PC-compatible computer. Stimuli were presented on a 60-Hz vertical retrace IKEGAMI DM516A (20-inch diagonal) monochrome graphics monitor with a fast, white P4-type phosphor. A special circuit that combines two output channels produces 4096 distinct gray levels (12 bits). The luminance of the monitor was 12.1 cd/m2 when every pixel was assigned the lowest gray level and 325 cd/m2 when every pixel was given the greatest gray level. The background luminance was set at 0.5 ∗ (325+12.1)=169 cd/m 2 . A lookup table was generated by means of a psychophysical procedure that linearly divided the whole luminance range into 256 gray levels. When extremely low contrasts were required by the experiment, a simpler lookup table was generated by linearly interpolating luminance levels around the background luminance (for contrasts less than 1%).
  119. M. S. Landy, Y. Cohen, and G. Sperling, “HIPS: a Unix-based image processing system,” Comput. Vis. Graph. Image Process. 25, 331–347 (1984a).
  120. M. S. Landy, Y. Cohen, and G. Sperling, “HIPS: image processing under UNIX software and applications,” Behav. Res. Methods Instrum. 16, 199–216 (1984b).
  121. R. S. Woodworth and H. Schlosberg, Experimental Psychology (Rev. ed.). (Holt, Rinehart & Winston, New York, 1954).
  122. H. R. Wilson, “Spatiotemporal characterization of a transient mechanism in the human visual system,” Vision Res. 20, 443–452 (1980).
  123. M. B. Mandler and W. Makous, “A three channel model of temporal frequency perception,” Vision Res. 24, 1881–1887 (1984).
  124. Z.-L. Lu and G. Sperling, “Sensitive calibration and measurement procedures based on the amplification principle in motion perception,” Vision Res. 41, 2355–2374 (2001).
  125. Z.-L. Lu and G. Sperling, “Black-white asymmetry in visual perception,” Mathematical Behavioral Sciences Rep. MBS 01–14 (University of California, Irvine, Calif., 2001).
  126. Apparatus. The stimuli were presented on an achromatic 19 Nanao FlexScan 6600 monitor, driven by the internal video card in a 7500/100 Power PC Macintosh at 120 frames/sec using a C++ version of VideoToolbox.127 A special circuit was used to combine two 8-bit output channels of the video card to produce 6144 distinct voltage levels (12.6 bits). A psychophysical procedure was used to generate a linear lookup table that evenly divides the entire dynamic range of the monitor (from 1 cd/m2 to 53 cd/m2) into 256 levels.
  127. D. G. Pelli and L. Zhang, “Accurate control of contrast on microcomputer displays,” Vision Res. 31, 1337–1350 (1991).
  128. O. I. Ukkonen and A. M. Derrington, “Motion of contrast-modulated gratings is analyzed by different mechanisms at low and at high contrasts,” Vision Res. 40, 3359–3371 (2000).
  129. “Feature tracking” is Ukkonen and Derrington’s128 term. However, a third-order motion system is required in order to do feature tracking. The terms are not synonymous. See Section 5.A.1.
  130. F. C. Kolb and J. Braun, “Blindsight in normal observers,” Nature 377, 336–338 (1995).
  131. P. Burt and G. Sperling, “Time, distance, and feature trade-offs in visual apparent motion,” Psychol. Rev. 88, 171–195 (1981).
  132. A. Baloch, S. Grossberg, E. Mingolla, and C. A. M. Nogueira, “Neural model of first-order and second-order motion perception and magnocellular dynamics,” J. Opt. Soc. Am. A 16, 953–978 (1999).
  133. M. J. Morgan and C. Chubb, “Contrast facilitation in motion detection: evidence for a Reichardt detector in human vision,” Vision Res. 39, 4217–4231 (1999).
  134. J. Krauskopf and X. Li, “Effect of contrast on detection of motion of chromatic and luminance targets: retina-relative and object-relative movement,” Vision Res. 39, 3346–3350 (1999).

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article

OSA is a member of CrossRef.

CrossCheck Deposited