Biomimetic Vision

Conventional vision systems based on mathematical algorithms tend to become very complicated and their hardware implementation requires powerful 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 an ideal 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 unique in that it seeks to combine a number of important areas: 

•  insect neurophysiological experiments to form accurate models
• algorithm development
• software implementation of algorithms (using Matlab and LabView)
• hardware implementation of algorithms, primarily in silicon chips (analog VLSI)

Much of our work is a collaboration between physiologists and electrical engineers. Further information on this collaboration can be found via a separate web page. We are also a major node of the University Computational Neuroscience Research Cluster. 

Our funding sources: Australian Research Council (ARC), Tanner Research Inc., US Airforce Office of Scientific Research (AFOSR), Sir Ross and Sir Keith Smith Fund, University of Adelaide, Defence Science and Technology Organisation (DSTO).