Low-Level Image Cues in the Perception of Translucent Materials

Abstract

When light strikes a translucent material (such as wax, milk or fruit flesh), it enters the body of the object, scatters and reemerges from the surface. The diffusion of light through translucent materials gives them a characteristic visual softness and glow. What image properties underlie this distinctive appearance? What cues allow us to tell whether a surface is translucent or opaque? Previous work on the perception of semitransparent materials was based on a very restricted physical model of thin filters [Metelli 1970; 1974a,b]. However, recent advances in computer graphics [Jensen et al. 2001; Jensen and Buhler 2002] allow us to efficiently simulate the complex subsurface light transport effects that occur in real translucent objects. Here we use this model to study the perception of translucency, using a combination of psychophysics and image statistics. We find that many of the cues that were traditionally thought to be important for semitransparent filters (e.g., X-junctions) are not relevant for solid translucent objects. We discuss the role of highlights, color, object size, contrast, blur, and lighting direction in the perception of translucency. We argue that the physics of translucency are too complex for the visual system to estimate intrinsic physical parameters by inverse optics. Instead, we suggest that we identify translucent materials by parsing them into key regions and by gathering image statistics from these regions.

References

1. Adelson, E. H. 1993. Perceptual organization and the judgement of brightness. Science 262, 5142, 2042--2044.
2. Adelson, E. H. 1999. Lightness perception and lightness illusions. In The New Cognitive Neurosciences, M. S. Gazzaniga, Ed. MIT Press, Cambridge, MA, 339--351.
3. Adelson, E. H. 2001. On seeing stuff: the perception of materials by humans and machines. In Proceedings of the SPIE. Volume 4299: Human Vision and Electronic Imaging VI, B. E. Rogowitz and T. N. Pappas, Eds. SPIE, Bellingham, WA, 1--12.
4. Adelson, E. H. and Anandan, P. 1990. Ordinal characteristics of transparency. In Proceedings of the AAAI-90 Workshop on Qualitative Vision. 77--81.
5. Anderson, B. 2001. Contrasting theories of White's illusion. Perception 30, 1499--1501.
6. Anderson, B. L. 1997. A theory of illusory lightness and transparency in monocular and binocular images: the role of contour junctions. Perception 26, 4, 419--453.
7. Anderson, B. L. 1999. Stereoscopic surface perception. Neuron 24, 991--928.
8. Anderson, B. L. 2003. The role of occlusion in the perception of depth, lightness, and opacity. Psychological Review 110, 4, 785--801.
9. Beck, J. 1972. Surface Color Perception. Cornell University Press, Ithaca, New York.
10. Beck, J. 1978. Additive and subtractive color mixture in color transparency. Perception and Psychophysics 23, 3, 265--267.
11. Beck, J. and Ivry, R. 1988. On the role of figural organization in perceptual transparency. Perception and Psychophysics 44, 6, 585--594.
12. Beck, J. and Prazdny, K. 1981. Highlights and the perception of glossiness. Perception and Psychophysics 30, 4, 407--410.
13. Beck, J., Prazdny, K., and Ivry, R. 1984. The perception of transparency with achromatic colors. Perception and Psychophysics 35, 5, 407--422.
14. Berzhanskaya, J., Swaminathan, G., Beck, J., and Mingolla, E. 2002. Highlights and surface gloss perception. Journal of Vision 2, 7, 93. (Vision Sciences Society conference abstract. VSS '02, Sarasota FL.)
15. Blake, A. and Bülthoff, H. H. 1990. Does the brain know the physics of specular reflection? Nature 343, 6254, 165--168.
16. Blake, A. and Bülthoff, H. H. 1991. Shape from specularities: Computation and psychophysics. Philosophical Transactions of the Royal Society (London) Series B 331, 237--252.
17. Bloj, M., Ripamonti, C., Mitha, K., Hauck, R., Greenwald, S., and Brainard, D. H. 2004. Does an equivalent illuminant model for the effect of surface slant on perceived lightness. Journal of Vision 4, 9, 735--746.
18. Brainard, D. H., Kraft, J. M., and Longère, P. 2003. Color constancy: developing empirical tests of computational models. In Colour Perception: From Light To Object, R. Mausfeld and D. Heyer, Eds. Oxford University Press, Oxford, UK, 307--334.
19. Chandrasekhar, S. 1960. Radiative Transfer. Oxford University Press, Oxford, UK.
20. Chen, J. V. and D'Zmura, M. 1998. Test of a convergence model for color transparency perception. Perception 27, 585--594.
21. Cornsweet, T. N. 1970. Visual Perception. Academic Press, New York.
22. Debevec, P. E. 1998. Rendering synthetic objects into real scenes: Bridging traditional and image-based graphics with global illumination and high dynamic range photography. In Proceedings of ACM SIGGRAPH 98. ACM Press/ACM SIGGRAPH, Computer Graphics Proceedings, Annual Conference Series, New York, 189--198.
23. Delahunt, P. B. and Brainard, D. H. 2004. Color constancy under changes in reflected illumination. Journal of Vision 4, 9, 764--778.
24. Doerschner, K., Boyaci, H., and Maloney, L. T. 2004. Human observers compensate for secondary illumination originating in nearby chromatic surfaces. Journal of Vision 4, 2, 92--105.
25. D'Zmura, M., Colantoni, P., Knoblauch, K., and Laget, B. 1997. Color transparency. Perception 26, 471--492.
26. D'Zmura, M., Rinner, O., and Gegenfurtner, K. R. 2000. The colors seen behind transparent filters. Perception 29, 911--926.
27. Fleming, R. W., Dror, R. O., and Adelson, E. H. 2003. Real-world illumination and the perception of surface reflectance properties. Journal of Vision 3, 5, 347--368.
28. Fleming, R. W., Jensen, H. W., and Bülthoff, H. H. 2004. Perceiving translucent materials. In Proceedings of APGV 2004: ACM SIGGRAPH Symposium on Applied Perception in Graphics and Visualization. ACM Press, New York, 127--134.
29. Fuchs, W. 1923a. Experimentelle Untersuchungen &uberuml; die &anderunguml; von Farben unter dem Einfluss von Gestalten. Zeitshcrift für Psychologie 92, 299--325.
30. Fuchs, W. 1923b. Untersuchungen &uberuml; das simultane Hintereinandersehen auf derselben Sehrichtung. Zeitshcrift für Psychologie 91, 195--235.
31. Gerbino, W. 1994. Achromatic transparency. In Lightness, Brightness and Transparency, A. L. Gilchrist, Ed. Lawrence Erlbaum, Hove, England, 215--255.
32. Gerbino, W., Stultiens, C. I., M., J., and de Weert, C. M. 1990. Transparent layer constancy. Journal of Experimental Psychology: Human Perception and Performance 16, 1, 3--20.
33. Gilchrist, A. L., Kossyfidis, C., Bonato, F., Agostini, T., Cataliotti, J., Li, X., Spehar, B., Annan, V., and Economou, E. 1999. An anchoring theory of lightness perception. Psychological Review 106, 795--834.
34. Hartline, H. K. 1940. The receptive fields of optic nerve fibres. American Journal of Physiology 130, 690--699.
35. Heeger, D. J. and Bergen, J. R. 1995. Pyramid-based texture analysis/synthesis. In Proceedings of ACM SIGGRAPH 95. ACM Press/ACM SIGGRAPH, Computer Graphics Proceedings, Annual Conference Series, New York, 229--238.
36. Heider, G. 1933. New studies in transparency, form and color. Psychologische Forschung 17, 13--55.
37. Hering, E. 1964. Outlines of a Theory of the Light Sense. Harvard University Press, Cambridge, MA. Original work published 1874. (Edition translated by L. M. Hurvich and D. Jameson.)
38. Hunter, R. S. 1975. The Measurement of Appearance. Wiley-Interscience, New York.
39. Jensen, H. W. 2001. Realistic Image Synthesis Using Photon Mapping. A K Peters, Natick, MA.
40. Jensen, H. W. and Buhler, J. 2002. A rapid hierarchical rendering technique for translucent materials. ACM Transactions of Graphics (SIGGRAPH 2002) 21, 3, 576--581.
41. Jensen, H. W., Marschner, S. R., Levoy, M., and Hanrahan, P. 2001. A practical model for subsurface light transport. In Proceedings of ACM SIGGRAPH 2001, E. Fiume, Ed. ACM Press/ACM SIGGRAPH, Computer Graphics Proceedings, Annual Conference Series, New York, 511--518.
42. Kanizsa, G. 1955. Condizioni ed effetti della transparenza fenomica. Revista di Psicologia 49, 3--19.
43. Katz, D. 1935. The World of Colour. Kegan Paul, London, UK.
44. Kersten, D. 1991. Transparency and the cooperative computation of scene attributes. In Computational Models of Visual Processing, M. S. Landy and J. A. Movshon, Eds. M.I.T. Press, Cambridge, MA, 209--228.
45. Kersten, D., Bülthoff, H. H., Schwartz, B., and Kurtz, K. 1992. Interaction between transparency and structure from motion. Neural Computation 4, 4, 573--589.
46. Khang, B. G. and Zaidi, Q. 2002a. Accuracy of color scission for spectral transparencies. Journal of Vision 2, 6, 451--466.
47. Khang, B. G. and Zaidi, Q. 2002b. Cues and strategies for color constancy: perceptual scission, image junctions and transformational color matching. Vision Research 42, 2, 211--226.
48. Koenderink, J. J. 2003. Guest editorial. another Babel. Perception 32, 391--394.
49. Koenderink, J. J. and van Doorn, A. J. 1980. Photometric invariants related to solid shape. Optica Acta 27, 7, 981--996.
50. Koenderink, J. J. and van Doorn, A. J. 2001. Shading in the case of translucent objects. In Proceedings of the SPIE. Volume 4299: Human Vision and Electronic Imaging VI, B. E. Rogowitz and T. N. Pappas, Eds. SPIE, Bellingham, WA, 312--320.
51. Koffka, K. 1935. Principles of Gestalt Psychology. Harcourt, New York.
52. Lindsey, D. T. and Todd, J. T. 1996. On the relative contributions of motion energy and transparency to the perception of moving plaids. Vision Research 36, 207--222.
53. Maloney, L. T. and Yang, J. N. 2003. The illumination estimation hypothesis and surface color perception. In Colour Vision: Connecting the mind to the physical world, R. Mausfeld and D. Heyer, Eds. Oxford University Press, Oxford, UK, 335-- 358.
54. Mamassian, P. and Kersten, D. 1996. Illumination, shading and the perception of local orientation. Vision Research 36, 15, 2351--2367.
55. Masin, S. C. 1997. The luminance conditions of transparency. Perception 26, 1, 39--50.
56. Masin, S. C. 1999a. Color scission and phenomenal transparency. Perceptual and Motor Skills 89, 815--823.
57. Masin, S. C. 1999b. Phenomenal transparency in achromatic checkerboards. Perceptual and Motor Skills 88, 2, 685--692.
58. Metelli, F. 1967. Zur Analyse der phänomenalen Durchscheintigkeitserschienungen. In Gestalt und Wirklichkeit, Festgabe für Ferdinand Weinhand. Duncker and Humboldt, Berlin, Germany.
59. Metelli, F. 1970. An algebraic development of the theory of perceptual transparency. Ergonomics 13, 1, 59--66.
60. Metelli, F. 1974a. Achromatic color conditions in the perception of transparency. In Perception, R. B. Macleod and H. L. Pick, Eds. Cornell University Press, Ithaca, New York, 95--116.
61. Metelli, F. 1974b. The perception of transparency. Scientific American 230, 4, 90--98.
62. Metelli, F., Da Pos, O., and Cavedon, A. 1985. Balanced and unbalanced, complete and partial transparency. Perception and Psychophysics 38, 4, 354--366.
63. Metzger, W. 1953. Gesetze des Sehens. W. Kramer, Frankfurt am Main, Germany.
64. Mingolla, E. and Todd, J. T. 1986. Perception of solid shape from shading. Biological Cybernetics 53, 137--151.
65. Moulden, B., Kingdom, F., and Gatley, L. F. 1990. The standard deviation of luminance as a metric for contrast in random-dot images. Perception 19, 79--101.
66. Nakayama, K. and Shimojo, S. 1992. Experiencing and perceiving visual surfaces. Science 257, 1357--1363.
67. Nakayama, K., Shimojo, S., and Ramachandran, V. S. 1990. Transparency: Relation to depth, subjective contours, luminance, and neon color spreading. Perception 19, 497--513.
68. Nishida, S. and Shinya, M. 1998. Use of image-based information in judgments of surface-reflectance properties. Journal of the Optical Society of America A15, 2951--2965.
69. Peli, E. 1990. Contrast in complex images. Journal of the Optical Society of America A7, 2032--2040.
70. Plummer, D. J. and Ramachandran, V. S. 1993. Perception of transparency in stationary and moving images. Spatial Vision 7, 2, 113--123.
71. Portilla, J. and Simoncelli, E. P. 2000. A parametric texture model based on joint statistics of complex wavelet coefficients. International Journal of Computer Vision 40, 1, 49--71.
72. Robilotto, R., Khang, B. G., and Zaidi, Q. 2002. Sensory and physical determinants of perceived achromatic transparency. Journal of Vision 2, 5, 388--403.
73. Robilotto, R. and Zaidi, Q. 2004. Perceived transparency of neutral density filters across dissimilar backgrounds. Journal of Vision 4, 3, 183--195.
74. Singh, M. 2004. Lightness constancy through transparency: Internal consistency in layered surface representations. Vision Research 44, 1827--1842.
75. Singh, M. and Anderson, B. L. 2002a. Perceptual assignment of opacity to translucent surfaces: the role of image blur. Perception 31, 5, 531--552.
76. Singh, M. and Anderson, B. L. 2002b. Toward a perceptual theory of transparency. Psychological Review 109, 3, 492--519.
77. Somers, D. C. and Adelson, E. H. 1997. Junctions, transparency, and brightness. Investigative Ophthalmology and Vision Science (Supplement) 38, 453.
78. Stoner, G. R., Albright, T. D., and Ramachandran, V. S. 1990. Transparency and coherence in human motion perception. Nature 344, 6262, 153--155.
79. Todd, J. T. and Mingolla, E. 1983. Perception of surface curvature and direction of illuminant from patterns of shading. Journal of Experimental Psychology: Human Perception and Performance 9, 583--595.
80. Tommasi, M. 1999. A ratio model of perceptual transparency. Perceptual and Motor Skills 89, 3, 891--897.
81. Tudor-Hart, B. 1928. Studies in transparency, form and color. Psychologische Forschung 10, 255--298.
82. von Helmholtz, H. 1962. Helmholtz's Treatise on Physiological Optics. Dover, New York. Original work published 1867. (Edition edited by J. P. C. Southall.)
83. Watanabe, T. and Cavanagh, P. 1992. The role of transparency in perceptual grouping and pattern recognition. Perception 21, 131--139.
84. Watanabe, T. and Cavanagh, P. 1993a. Surface decomposition accompanying the perception of transparency. Spatial Vision 7, 2, 95--111.
85. Watanabe, T. and Cavanagh, P. 1993b. Transparent surfaces defined by implicit X junctions. Vision Research 33, 16, 2339--2346.

Index Terms

• Applied computing

  • Law, social and behavioral sciences

• Computing methodologies

  • Artificial intelligence

    • Computer vision

      • Computer vision problems

      • Computer vision tasks

        • Scene understanding

  • Computer graphics

    • Image manipulation

      • Texturing