Koch, Christof and Luo, Jin and Mead, Carver and Hutchinson, James (1988) Computing Motion Using Resistive Networks. In: Neural Information Processing Systems. American Institute of Physics , New York, NY, pp. 422-431. ISBN 0883185695 http://resolver.caltech.edu/CaltechAUTHORS:20160107-154149599
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To us, and to other biological organisms, vision seems effortless. We open our eyes and we "see" the world in all its color, brightness, and movement. Yet, we have great difficulties when trying to endow our machines with similar abilities. In this paper we shall describe recent developments in the theory of early vision which lead from the formulation of the motion problem as an ill-posed one to its solution by minimizing certain "cost" functions. These cost or energy functions can be mapped onto simple analog and digital resistive networks. Thus, we shall see how the optical flow can be computed by injecting currents into resistive networks and recording the resulting stationary voltage distribution at each node. These networks can be implemented in cMOS VLSI circuits and represent plausible candidates for biological vision systems.
|Item Type:||Book Section|
|Additional Information:||© American Institute of Physics 1988. An early version of this model was developed and implemented in collaboration with A. L. Yuille, M. Avalos and A. Hsu wrote the code for the Imaging Technology system and E. Staats for the NCUBE. C.K. is supported by an ONR Research Young Investigator Award and by the Sloan and the Powell Foundations. C.M. is supported by ONR and by the System Development Foundation. A portion of this research was carried out at the Jet Propulsion Laboratory and was sponsored by NSF grant No. EET-8714710, and by NASA.|
|Group:||Koch Laboratory, KLAB|
|Usage Policy:||No commercial reproduction, distribution, display or performance rights in this work are provided.|
|Deposited By:||Kristin Buxton|
|Deposited On:||19 Jan 2016 22:43|
|Last Modified:||19 Jan 2016 22:43|
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