Parametric Study of Diffusion-Enhancement Networks for Spatiotemporal Grouping in Real-Time Artificial Vision
Annual technical summary rept. Apr 1991-Jun 1992
MASSACHUSETTS INST OF TECH LEXINGTON LINCOLN LAB
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This is the second Annual Technical Summary of the MIT Lincoln Laboratory parametric study of diffusion-enhancement networks for spatiotemporal grouping in real-time artificial vision. Spatiotemporal grouping phenomena are examined in the context of static and time-varying imagery. Dynamics that exhibit static feature grouping on multiple scales as a function of time, and long-range apparent motion between time-varying inputs, are developed for a biologically plausible diffusion-enhancement layer coupled by feedforward and feedback connections input is provided by a separate feature-extracting layer. The model is cast as an analog circuit that is realizable in VLSI, the parameters of which are selected to satisfy a psychophysical data base on apparent motion.
- Anatomy and Physiology