The Math of a Fly's Eye May Prove Useful

cunniff writes "Wired Magazine points us to recent research that demonstrates an algorithm derived from the actual biological implementation of fly vision (PLoS paper here). Quoting the paper: 'Here we present a model with multiple levels of non-linear dynamic adaptive components based directly on the known or suspected responses of neurons within the visual motion pathway of the fly brain. By testing the model under realistic high-dynamic range conditions we show that the addition of these elements makes the motion detection model robust across a large variety of images, velocities and accelerations.' The researchers claim that 'The implementation of this new algorithm could provide a very useful and robust velocity estimator for artificial navigation systems.' Additionally, the paper describes the algorithm as extremely simple, capable of being implemented on very small and power-efficient processors. Best of all, the entire paper is public and hosted via a service that allows authenticated users to give feedback."

Comments

Anyone know about bees?

[hatemonger]

The researchers drew their algorithm from neural circuits attuned to side-to-side yaw, but O’Carroll said the same types of equations are probably used in computing other optical flows, such as those produced by moving forward and backwards through three-dimensional space.

I vaguely remember seeing a study that examined how bees travel without hitting anything but using very few neurons. Something about the relative size change of objects between eyes. They tested this by putting bees in a clear tunne with patterns on belts on the right and left walls. By changing the speed of the belts, the bees would ram into the walls, but as long as the belts were moving at the same speed, the bees were fine. Is this ringing a bell for anyone else?