Abstract
Visual experience is intrinsically subjective. The manifest unity of our perceptions belies the indeterminacy of our sensations. A single pattern of excitation on the retinal receptors is consistent with many possible worlds of objects. The simple problem of determining object brightness exemplifies the ambiguities inherent in the retinal image. The photons incident on a given receptor may indicate the presence of a bright or dark object depending on the overall level of illumination. In mediating automatic gain control, the horizontal cells of the retina express an assumption about the nature of the illuminant. These neurons in the most peripheral part of the visual system take the first step toward interpretation of the image. By a process of lateral inhibition, they discount the effect of illumination and determine the brightness of an object relative to that of nearby objects. At all levels of complexity, the visual system interprets each data point within the context of the scene. This interpretation is consistent with the input data and with the internal structure of the system. Through evolution, the structure of the visual system provides correspondence between the mental image and the objective world.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Ballard, D.H. (1986). Cortical connections and parallel processing: Structure and function. The Behavioral and Brain Sciences 9: 67–120.
Burr, D.C., and Ross, J. (1979). How does binocular delay give information about depth? Vision Research 19: 523–532.
Delbrück, T., and Mead, C.A. (1989). An electronic photoreceptor sensitive to small changes in intensity. In Touretsky, D. S. (ed), Advances in Neural Information Processing Systems 1., pp 712–727, San Mateo, CA: Morgan Kaufman.
Gardner, J.C., Douglas, R.M., and Cyander, M.S. (1985). A time-based stereoscopic depth mechanism in the visual cortex. Brain Research 328: 154–157.
Hutchinson, J., Koch, C., Luo, J., and Mead, C. (1988). Computing motion using analog and binary resistive networks. IEEE Computer March pp. 52–63.
Julesz, B. (1960). Binocular depth perception of computer-generated patterns. Bell Syst. Tech. J. 39: 1125–1162.
Julesz, B. (1971). Foundations of Cyclopean Perception. Chicago, IL: The University of Chicago Press.
Lazzaro, J., Ryckebusch S., Mahowald, M.A., and Mead, C.A. (1989). Winner-Take-All circuits of O(n) complexity. In Touretsky, D.S. (ed), Advances in Neural Information Processing Systems 1. pp. 703–711, San Mateo, CA: Morgan Kaufman.
Mahowald, M.A. and Mead, C.A. (1989). Silicon retina. In Mead, C.A. Analog VLSI and Neural Systems, pp. 257–278, Reading, MA: Addison-Wesley.
Marr, D., Palm, G., and Poggio, T. (1978). Analysis of a cooperative stereo algorithm. Biological Cybernetics 28: 223–239.
Marr, D., and Poggio, T. (1976). Cooperative computation of stereo disparity. Science 194: 283–287.
Marr, D. (1982). Vision, New York: W. H. Freeman.
Mayhew, J. and Frisby, J.P. (1981). Psychophysical and computational studies towards a theory of human stereopsis. Artificial Intelligence 17: 349–385.
Mead, C.A. (1989). Analog VLSI and Neural Systems. Reading, MA: Addison-Wesley.
Mead, C.A. and Mahowald, M.A. (1988). A silicon model of early visual processing. Neural Networks. 1: 91–97.
Nishihara, H. (1984). Practical real-time imaging stereo matcher. Optical Engineering 23: 536–545.
Poggio, G. (1984). Processing of stereoscopic information in primate visual cortex. In Edelman, G. M., Gall W. E., and Cowan, W. M. (eds), Dynamic aspects of neocortical function, pp. 613–635, New York: John Wiley & Sons.
Poggio, G. and Poggio, T. (1984). The analysis of stereopsis. Annual Review of Neuroscience 7: 379–412.
Shimojo, S., Silverman, G.H., and Nakayama, K. (1985). An occlusion-related mechanism of depth perception based on motion and interocular sequence. Nature 333: 265–268.
Sivilotti, M.A., Mahowald, M.A., and Mead, C.A. (1987). Real-time visual computations using analog CMOS processing arrays. In Losleben, (ed), Advanced Research in VLSI, Proceedings of the 1987 Stanford Conference, pp. 295–312, Cambridge, MA: MIT Press.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1989 Kluwer Academic Publishers
About this chapter
Cite this chapter
Mahowald, M.A., Delbrück, T. (1989). Cooperative Stereo Matching Using Static and Dynamic Image Features. In: Mead, C., Ismail, M. (eds) Analog VLSI Implementation of Neural Systems. The Kluwer International Series in Engineering and Computer Science, vol 80. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1639-8_9
Download citation
DOI: https://doi.org/10.1007/978-1-4613-1639-8_9
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4612-8905-0
Online ISBN: 978-1-4613-1639-8
eBook Packages: Springer Book Archive