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."
After presenting his paper, researcher David O'Carroll strode off the stage and into a sliding glass door.
-Peter
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?
Look, you've got to at least RTFS.
Why does this sound like every PC user and quite a few programmers I have had to deal with?
I find it unimaginable that people would attempt to implement a technology that is not fully understood. Doing so will eventually yield unexpected results or at the very least, results that cannot be explained.
I am not saying that everything we presently or regularly do is something that everyone presently understands as I am sure there are ample examples of this happening everywhere. Usually, however, "someone" somewhere actually knows and understands because they created it. In this case, it seems, things are being created and implemented without a full working understanding of how it all works. At the very least, such inventions should be unworthy of patenting.
Though they built the system, the researchers don’t quite understand how it works.
and...
Intriguingly, the algorithm doesn’t work nearly as well if any one operation is omitted. The sum is greater than the whole, and O’Carroll and Brinkworth don’t know why.
Wow, some interesting "science" that's going on here.
Great result, but, really, way to go guys! You can't understand a non-linear system's behavior; join the club. I still can't understand why z_n+1 = z_n^2 + c looks so pretty either.
But where's the source code???
And if God had intended for Man to drink beer we would have been born with stomachs.
We've implemented this algorithm in several autonomous flying surveillance vehicles. While it appears to work adequately, we're still trying to determine why the only thing they manage to locate is cow shit.
Have gnu, will travel.
"Fly" programming language ...and just like the original thing, it has garbage collection!
-- Terry
This might be offtopic but seeing a legitimate R&D story on slashdot with a link to the actual (open) technical write up of the research made my day. I haven't read the whole paper yet (I will when I get home) but going through it and reading the first few sections I can see that the researchers included their (simulink?) processing models as well as some good data in the results section. This story finally gave me something worth breaking out my old signal processing and DAC notes from college out over and studying the raw math and theory behind the algorithm.
I have to say, I really wish we would see more papers like this posted and published openly. It's very inspiring when other folk in similar fields can access a paper's full contents and start playing with similar models themselves...
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