Computing Motion Using Resistive Networks
Koch, Christof, Luo, Jin, Mead, Carver, Hutchinson, James
–Neural Information Processing Systems
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 illposed oneto 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. APERTURE PROBLEM AND SMOOTHNESS ASSUMPTION In this study, we use intensity-based schemes for recovering motion.
Neural Information Processing Systems
Dec-31-1988
- Country:
- North America > United States
- California (0.15)
- Massachusetts > Middlesex County (0.14)
- North America > United States
- Industry:
- Semiconductors & Electronics (0.35)
- Technology:
- Information Technology > Artificial Intelligence
- Machine Learning (0.68)
- Vision (0.51)
- Information Technology > Artificial Intelligence