• Electrophysiological recordings from insect neurons that detect and track moving targets and features
• Biomimetic modeling/algorithm development based on insect visual neurobiology.
• Neuromorphic analog VLSI.

Conventional vision systems based on mathematical algorithms tend to become very complicated and their hardware implementation requires no less than powerful main-frame computers to run in real time. Biological models of the insect visual system, however, suggest simpler solutions for constrained tasks, like motion detection. Insects are a model system because they display sophisticated flight control and yet are simple enough that we have been able to deduce a great deal about the underlying neural circuitry used for such tasks, using physiological techniques. The insect vision group at the University of Adelaide uses a truly cross-disciplinary approach to transfer ideas derived from studying insect physiology and behaviour to robust models in software and hardware.

This program is a world-first in that it seeks to combine a number of important areas:

• insect neurophysiological experiments to form accurate models,
• algorithm development
• hardware implementation of algorithms (primarily in analog VLSI)
• study of stochastic resonance to improve neural models,
• algorithm extension to colour vision to exploit redundancy/error checking
• implementation with millimetre-wave front end for all-weather outdoor performance.

On the VLSI side we have developed novel circuits for early visual processing. A few to be mentioned are: a current mode spatial averaing (CMSA), a multiplicative noise cancellation (MNC) circuit, a wide dynamic range current mode fusing resistive circuit, and a very low (10^-11 Siemens) transconductive element based on the Early effect. In many of these cases we have exploited subthreshold circuits, mainly to use the exponential relationship of the current-voltage and also to reduce the power dissipation. Our new patented approach uses an active impedance transformation to convert a voltage controlled grounded resistor into a floating resistor.

A major focus of our present work is the task of motion detection, for analysis of optic flow and estimation of the speed of moving targets and features. We have designed and implemented a series of analog VLSI chips based on an insect-inspired motion detection algorithm, the template model. Since the first chip (Bugeye I in 1992), we have designed several other chips, namely, Bugeye II, Bugeye III-1, Bugeye III-2, Bugeye IV, MNCSI (the first full implementation of shunting inhibition), and Bugeye V. We have used various processes from 2.0 to 0.8u for fabrication, all from MOSIS (simply because it is the best hassle free fabrication service, though a bit more expensive than some other options). In collaboration with Tanner Research Inc. in the USA , we are now developing new implementations based on an adaptive elaborated Reichardt model for a correlation-based motion detector, using the silicon on sapphire (SOS) process.