Abstract
There are two key elements in defining the problem of visual perception. The first is that useful information about the world, such as the shape, material, illumination, and spatial relationships of objects, is encrypted in the image. Second, the encryption process, of going from a description of the world to an image, is not in general reversible. Any single source of image information is usually ambiguous about its causes in the scene. Seeing is the process of decoding the image information. 3-D computer graphics simulates the process of encrypting scene information into the image. By creating images from synthetic scenes, we can gain insights into the constraints used by the visual system to decode image information, and we can begin to bridge the gap between the simple images of the laboratory and complex natural scenes. Computer graphics modeling and animation tools provide the means to generate stills and animations that produce strong perceptual interpretations, yet are theoretically indeterminate. I will describe several illusions involving computer renderings and animations that illustrate the constraints human perception uses to solve ambiguity about material, shape, and depth.
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Adelson, E. H. (1993). Perceptual organization and the judgment of brightness.Science,262, 2042–2044.
Adelson, E. H., &Pentland, A. P. (1991). The perception of shading and reflectance. In B. Blum (Ed.),Channels in the visual nervous system (pp. 195–207). London: Freud Publishing.
Buckley, D., Frisby, J. P., &Freeman, J. (1994). Lightness perception can be affected by surface curvature from stereopsis.Perception,23, 869–881.
Bui-Tuong, P. (1975). Illumination for computer generated pictures.Communications of the ACM,18, 311–317.
Bülthoff, H. H., &Edelman, S. (1993). Evaluating object recognition theories by computer graphics psychophysics. In T. A. Poggio & D. A. Glaser (Eds.),Exploring brain functions: Models in neuroscience (pp. 139–164). New York: Wiley.
Bülthoff, H. H., &Mallot, H. A. (1988). Integration of depth modules: Stereo and shading.Journal of the Optical Society of America A,5, 1749–1758.
Bülthoff, H. H., &Yuille, A. L. (1991). Bayesian models for seeing shapes and depth.Comments on Theoretical Biology,2, 283–314.
Canny, J. F. (1986). A computational approach to edge detection.IEEE Transactions on Pattern Analysis & Machine Intelligence,8, 679–698.
Cavanagh, P. (1987). Reconstructing the third dimension: Interactions between color, texture, motion, binocular disparity and shape.Computer Vision, Graphics, & Image Processing,37, 171–195.
Christou, C., &Parker, A. (1995). Visual realism and virtual reality: A psychological perspective. In K. Carr & R. England (Eds.),Simulated and virtual realities: Elements of perception (pp. 53–84). Bristol, U.K.: Taylor & Francis.
Cook, R., &Torrance, K. (1982). A reflectance model for computer graphics.ACM Transactions on Graphics,1, 7–24.
Cutting, J., &Vishton, P. (1995). Perceiving layout and knowing distances: The integration, relative potency, and contextual use of different information about depth. In W. Epstein & S. J. Rogers (Eds.),Perception of space and motion (pp. 69–117). San Diego: Academic Press.
Distler, H. (1996). Psychophysical experiments in virtual environments.Virtual Reality World ’96, pp. 1–11. Available: www.mpiktueb.mpg.de/projects/bicycle/vrworld/poster.html
Foley, J. D., van Dam, A., Feiner, S. K., &Hughes, J. F. (1990).Computer graphics: Principles and practice (2nd ed.). Reading, MA: Addison-Wesley.
Gauthier, I., &Tarr, M. J. (in press). Becoming a “Greeble” expert: Exploring mechanisms for face recognition.Vision Research.
Greenberg, D. P. (1989). Light reflection models for computer graphics.Science,244, 166–173.
Hallinan, P. W. (1995).A deformable model for the recognition of human faces under abitrary illumination. Unpublished doctoral dissertation, Harvard University.
Hurlbert, A. (1986). Formal connections between lightness algorithms.Journal of the Optical Society of America A,3, 1684–1693.
Hurlbert, A. C. (1995).Computational models of colour constancy (Rep. No. NCSS TR 95-04). University of Newcastle upon Tyne, Neural Computation and Sensory Systems Research Group.
Kersten, D. (1990). Statistical limits to image understanding. In C. Blakemore (Ed.),Vision: Coding and efficiency (pp. 32–44). Cambridge: Cambridge University Press.
Kersten, D., Knill, D., Mamassian, P., &Bülthoff, I. (1996). Illusory motion from shadows.Nature,379, 31.
Knill, D. C., &Kersten, D. (1991). Apparent surface curvature affects lightness perception.Nature,351, 228–230.
Knill, D. C., &Richards, W. (Eds.) (1996).Perception as Bayesian inference. Cambridge: Cambridge University Press.
Land, E. H., &McCann, J. (1971). Lightness and retinex theory.Journal of the Optical Society of America A,61, 1–11.
Langer, M. S., &Zucker, S. W. (1994). Shape-from-shading on a cloudy day.Journal of the Optical Society of America A,11, 467–478.
Lee, D. N., &Reddish, P. E. (1981). Plummeting gannets: A paradigm of ecological optics.Nature,293, 293–294.
Mamassian, P., Kersten, D., &Knill, D. C. (1996). Categorical local shape perception.Perception,25, 95–107.
Nakayama, K., Shimojo, S., &Ramachandran, V. S. (1990). Transparency: Relation to depth, subjective contours, luminance, and neon color spreading.Perception,19, 497–513.
Nayar, S. K., &Oren, M. (1995). Visual appearance of matte surfaces.Science,267, 1153–1156.
Regan, D. (1986). Visual processing of four kinds of relative motion.Vision Research,26, 127–145.
Sinha, P., &Adelson, E. (1993). Recovering reflectance and illumination in a world of painted polyhedra.Proceedings of Fourth International Conference on Computer Vision (pp. 156–163). (Conference held in Berlin, May 1993).
Todd, J. T., &Mingolla, E. (1983). Perception of surface curvature and direction of illumination from patterns of shading.Journal of Experimental Psychology: Human Perception & Performance,9, 583–595.
Vetter, T., &Troje, N. F. (1995).A separated linear shape and texture space for modeling two-dimensional images of human faces (MPI-Memo No. 15). Tübingen: Max Planck Institute for Biological Cybernetics. Available: ftp://ftp.mpik-tueb.mpg.de/pub/mpimemos/TR-015.ps.Z
Yonas, A., Goldsmith, L. T., &Hallstrom, J. L. (1978). Development of sensitivity to information provided by cast shadows in pictures.Perception,7, 333–341.
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I thank Cindee Madison for useful comments and suggestions. This research was supported by NSF Grant SBR-9631682.
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Kersten, D. Inverse 3-D graphics: A metaphor for visual perception. Behavior Research Methods, Instruments, & Computers 29, 37–46 (1997). https://doi.org/10.3758/BF03200564
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DOI: https://doi.org/10.3758/BF03200564