Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-27T21:49:33.608Z Has data issue: false hasContentIssue false
  • English
  • Français

Three-dimensional shape perception from chromatic orientation flows

Published online by Cambridge University Press:  06 September 2006

QASIM ZAIDI  and
ANDREA LI
QASIM ZAIDI
Affiliation:
SUNY College of Optometry, Department of Vision Sciences, New York, New York
ANDREA LI
Affiliation:
Queens College, CUNY, Department of Psychology, Flushing, New York
Get access Rights & Permissions [Opens in a new window]

Abstract

The role of chromatic information in 3-D shape perception is controversial. We resolve this controversy by showing that chromatic orientation flows are sufficient for accurate perception of 3-D shape. Chromatic flows required less cone contrast to convey shape than did achromatic flows, thus ruling out luminance artifacts as a problem. Luminance artifacts were also ruled out by a protanope's inability to see 3-D shape from chromatic flows. Since chromatic orientation flows can only be extracted from retinal images by neurons that are responsive to color modulations and selective for orientation, the psychophysical results also resolve the controversy over the existence of such neurons. In addition, we show that identification of 3-D shapes from chromatic flows can be masked by luminance modulations, indicating that it is subserved by orientation-tuned neurons sensitive to both chromatic and luminance modulations.

Keywords

Three-dimensional shapeColorOrientation flows
Type
SURFACE COLOR PERCEPTION
Information
Visual Neuroscience , Volume 23 , Issue 3-4 , May 2006 , pp. 323 - 330
Copyright
© 2006 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Anstis, S. & Cavanagh, P. (1983). A minimum motion technique for judging equiluminance. In Colour Vision: Psychophysics and Physiology, eds. Mollon, J.D. & Sharpe, L.T., pp. 155–166. London: Academic Press.
Ben-Shahar, O. & Zucker, S.W. (2001). On the perceptual organization of texture and shading flows: From a geometrical model to coherence computation. In >IEEE Conference on Computer Vision and Pattern Recognition (CVPR01). Hawaii: Kauai.
Bradley, A., Switkes, E., & De Valois, K. (1988). Orientation and spatial frequency selectivity of adaptation to color and luminance gratings. Vision Research 28, 841–856.CrossRefGoogle Scholar
Breton, P., Iverson, L., Langer, M., & Zucker, S.W. (1992). Shading flows and Scenel bundles: A new approach to shape from shading. In Second European Conference on Computer Vision (ECCV92), ed. Sandini, S., pp. 135–150. New York: Springer-Verlag.
Brincat, S.L. & Connor, C.E. (2004). Underlying principles of visual shape selectivity in posterior inferotemporal cortex. Nature Neuroscience 7, 880–886.CrossRefGoogle Scholar
Buchsbaum, G. & Goldstein, J.L. (1979). Optimum probabilistic processing in colour perception. I. Colour discrimination. Proceedings of the Royal Society B (London) 205, 229–247.CrossRefGoogle Scholar
Cavanagh, P. (1991). Vision at equiluminance. In Vision and Visual Dysfunction Volume V: Limits of Vision, eds. Kulikowski, J.J. & Walsh, V., pp. 234–250. Boca Raton, Florida: CRC Press.
Caywood, M.S., Willmore, B., & Tolhurst, D.J. (2004). Independent components of color natural scenes resemble V1 neurons in their spatial and color tuning. Journal of Neurophysiology 91, 2859–2873.CrossRefGoogle Scholar
Clifford, C.W., Spehar, B., Solomon, S.G., Martin, P.R., & Zaidi, Q. (2003). Interactions between color and luminance in the perception of orientation. Journal of Vision 3, 106–115.Google Scholar
Delorme, A., Richard, G., & Fabre-Thorpe, M. (2000). Ultra-rapid categorisation of natural scenes does not rely on colour cues: a study in monkeys and humans. Vision Research 40, 2187–2200.CrossRefGoogle Scholar
Derrington, A.M., Krauskopf, J., & Lennie, P. (1984). Chromatic mechanisms in lateral geniculate nucleus of macaque. Journal of Physiology 357, 241–265.CrossRefGoogle Scholar
Edwards, R., Xiao, D., Keysers, C., Foldiak, P., & Perrett, D. (2003). Color sensitivity of cells responsive to complex stimuli in the temporal cortex. Journal of Neurophysiology 90, 1245–1256.CrossRefGoogle Scholar
Engel, S., Zhang, X., & Wandell, B. (1997). Colour tuning in human visual cortex measured with functional magnetic resonance imaging. Nature 388, 68–71.CrossRefGoogle Scholar
Flanagan, P., Cavanagh, P., & Favreau, O.E. (1990). Independent orientation-selective mechanisms for the cardinal directions of colour space. Vision Research 30, 769–778.CrossRefGoogle Scholar
Fleming, R.W., Torralba, A., & Adelson, E.H. (2004). Specular reflections and the perception of shape. Journal of Vision 4, 798–820.CrossRefGoogle Scholar
Flitcroft, D.I. (1989). The interactions between chromatic aberration, defocus and stimulus chromaticity: Implications for visual physiology and colorimetry. Vision Research 29, 349–360.CrossRefGoogle Scholar
Friedman, H.S., Zhou, H., & von der Heydt, R. (2003). The coding of uniform colour figures in monkey visual cortex. Journal of Physiology 548, 593–613.CrossRefGoogle Scholar
Gegenfurtner, K.R., Kiper, D.C., Beusmans, J.M., Carandini, M., Zaidi, Q., & Movshon, J.A. (1994). Chromatic properties of neurons in macaque MT. Visual Neuroscience 11, 455–466.CrossRefGoogle Scholar
Gegenfurtner, K.R., Kiper, D.C., & Levitt, J.B. (1997). Functional properties of neurons in macaque area V3. Journal of Neurophysiology 77, 1906–1923.Google Scholar
Hubel, D.H. & Wiesel, T.N. (1962). Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. Journal of Physiology 160, 106–154.CrossRefGoogle Scholar
Hubel, D.H. & Wiesel, T.N. (1968). Receptive fields and functional architecture of monkey striate cortex. Journal of Physiology 195, 215–243.CrossRefGoogle Scholar
Johnson, E.N., Hawken, M.J., & Shapley, R. (2001). The spatial transformation of color in the primary visual cortex of the macaque monkey. Nature Neuroscience 4, 409–416.CrossRefGoogle Scholar
Johnson, E.N., Hawken, M.J., & Shapley, R. (2004). Cone inputs in macaque primary visual cortex. Journal of Neurophysiology 91, 2501–2514.CrossRefGoogle Scholar
Kingdom, F.A. (2003). Color brings relief to human vision. Nature Neuroscience 6, 641–644.CrossRefGoogle Scholar
Kingdom, F.A., Beauce, C., & Hunter, L. (2004). Colour vision brings clarity to shadows. Perception 33, 907–914.CrossRefGoogle Scholar
Kiper, D.C. (2003). Colour and form in the early stages of cortical processing. Journal of Physiology 548, 335.CrossRefGoogle Scholar
Kiper, D.C., Fenstemaker, S.B., & Gegenfurtner, K.R. (1997). Chromatic properties of neurons in macaque area V2. Visual Neuroscience 14, 1061–1072.CrossRefGoogle Scholar
Knill, D.C. (2001). Contour into texture: Information content of surface contours and texture flow. Journal of the Optical Society of America A 18, 12–35.CrossRefGoogle Scholar
Kobatake, E. & Tanaka, K. (1994). Neuronal selectivities to complex object features in the ventral visual pathway of the macaque cerebral cortex. Journal of Neurophysiology 71, 856–867.Google Scholar
Koenderink, J.J. (1984). What does the occluding contour tell us about solid shape? Perception 13, 321–330.Google Scholar
Lee, B.B., Martin, P.R., & Valberg, A. (1988). The physiological basis of heterochromatic flicker photometry demonstrated in the ganglion cells of the macaque retina. Journal of Physiology 404, 323–347.CrossRefGoogle Scholar
Lennie, P., Krauskopf, J., & Sclar, G. (1990). Chromatic mechanisms in striate cortex of macaque. Journal of Neuroscience 10, 649–669.Google Scholar
Leventhal, A.G., Thompson, K.G., Liu, D., Zhou, Y., & Ault, S.J. (1995). Concomitant sensitivity to orientation, direction, and color of cells in layers 2, 3, and 4 of monkey striate cortex. Journal of Neuroscience 15, 1808–1818.Google Scholar
Li, A. & Zaidi, Q. (2000). Perception of three-dimensional shape from texture is based on patterns of oriented energy. Vision Research 40, 217–242.CrossRefGoogle Scholar
Li, A. & Zaidi, Q. (2001). Veridicality of three-dimensional shape perception predicted from amplitude spectra of natural textures. Journal of the Optical Society of America A 18, 2430–2447.CrossRefGoogle Scholar
Li, A. & Zaidi, Q. (2003). Observer strategies in perception of 3-D shape from isotropic textures: Developable surfaces. Vision Research 43, 2741–2758.CrossRefGoogle Scholar
Li, A. & Zaidi, Q. (2004). Three-dimensional shape from non-homogeneous textures: Carved and stretched surfaces. Journal of Vision 4, 860–878.CrossRefGoogle Scholar
Linsker, R. (1989). How to generate ordered maps by maximizing the mutual information between input and output signals. Neural Computation 1, 1402–1411.Google Scholar
Livingstone, M. & Hubel, D. (1988). Segregation of form, color, movement, and depth: anatomy, physiology, and perception. Science 240, 740–749.CrossRefGoogle Scholar
Livingstone, M.S. & Hubel, D.H. (1984). Anatomy and physiology of a color system in the primate visual cortex. Journal of Neuroscience 4, 309–356.Google Scholar
Logothetis, N.K. (2003). The underpinnings of the BOLD functional magnetic resonance imaging signal. Journal of Neuroscience 23, 3963–3971.Google Scholar
Ohki, K., Chung, S., Ch'ng, Y.H., Kara, P., & Reid, R.C. (2005). Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex. Nature 433, 597–603.CrossRefGoogle Scholar
Op de Beeck, H., Wagemans, J., & Vogels, R. (2001). Inferotemporal neurons represent low-dimensional configurations of parameterized shapes. Nature Neuroscience 4, 1244–1252.CrossRefGoogle Scholar
Parraga, C.A., Troscianko, T., & Tolhurst, D.J. (2002). Spatiochromatic properties of natural images and human vision. Current Biology 12, 483–487.CrossRefGoogle Scholar
Pearson, P.M. & Kingdom, F.A. (2002). Texture-orientation mechanisms pool colour and luminance contrast. Vision Research 42, 1547–1558.CrossRefGoogle Scholar
Regan, B.C., Julliot, C., Simmen, B., Vienot, F., Charles-Dominique, P., & Mollon, J.D. (1998). Frugivory and colour vision in Alouatta seniculus, a trichromatic platyrrhine monkey. Vision Research 38, 3321–3327.CrossRefGoogle Scholar
Sachtler, W. & Zaidi, Q. (1992). Chromatic and luminance signals in visual memory. Journal of the Optical Society of America A 9, 877–894.CrossRefGoogle Scholar
Scharff, L.V. & Geisler, W.S. (1992). Stereopsis at isoluminance in the absence of chromatic aberrations. Journal of the Optical Society of America A 9, 868–876.CrossRefGoogle Scholar
Shapley, R. & Hawken, M. (2002). Neural mechanisms for color perception in the primary visual cortex. Current Opinions in Neurobiology 12, 426–432.CrossRefGoogle Scholar
Sun, H., Smithson, H., Lee, B., & Zaidi, Q. (2006). Specificity of cone inputs to macaque retinal ganglion cells. Journal of Neurophysiology 95, 837–849.Google Scholar
Taylor, A.H. & Kerr, G.P. (1941). The distribution of energy in the visible spectrum of daylight. Journal of the Optical Society of America 31, 3–8.CrossRefGoogle Scholar
Thorell, L.G., De Valois, R.L., & Albrecht, D.G. (1984). Spatial mapping of monkey V1 cells with pure color and luminance stimuli. Vision Research 24, 751–769.CrossRefGoogle Scholar
Treue, S., Hol, K., & Rauber, H.J. (2000). Seeing multiple directions of motion-physiology and psychophysics. Nature Neuroscience 3, 270–276.CrossRefGoogle Scholar
Troscianko, T., Montagnon, R., Le Clerc, J., Malbert, E., & Chanteau, P.L. (1991). The role of colour as a monocular depth cue. Vision Research 31, 1923–1929.CrossRefGoogle Scholar
Ts'o, D.Y. & Gilbert, C.D. (1988). The organization of chromatic and spatial interactions in the primate striate cortex. Journal of Neuroscience 8, 1712–1727.Google Scholar
Tse, P.U. (2002). A contour propagation approach to surface filling-in and volume formation. Psychological Reviews 109, 91–115.Google Scholar
Wagner, G. & Boynton, R.M. (1972). Comparison of four methods of heterochromatic photometry. Journal of the Optical Society of America 62, 1508–1515.CrossRefGoogle Scholar
Wassle, H. & Boycott, B.B. (1991). Functional architecture of the mammalian retina. Physiological Reviews 71, 447–480.Google Scholar
Zaidi, Q. (1997). Decorrelation of L- and M-cone signals. Journal of the Optical Society of America A 14, 3430–3431.CrossRefGoogle Scholar
Zaidi, Q. & Li, A. (2002). Limitations on shape information provided by texture cues. Vision Research 42, 815–835.CrossRefGoogle Scholar
Zaidi, Q., Pokorny, J., & Smith, V. (1989). Sources of individual differences in anomaloscope equations for tritan defects. Clinical Vision Sciences 4, 89–94.Google Scholar