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Graphics Software Science

Student Maps Brain to Image Search 72

StonyandCher writes to mention that a University of Ottawa grad student is creating a search engine for visual images that will be powered by a system mapped from the human brain. "Woodbeck said he has already created a prototype of the search engine based on his patent, which apes the way the brain processes visual information and tries to take advantage of currently-available graphics processing capabilities in PCs. 'The brain is very parallel. There's lots of things going on at once,' he said. 'Graphics processors are also very parallel, so it's a case of almost mapping the brain onto graphics processors, getting them to process visual information more effectively.'"
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Student Maps Brain to Image Search

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  • by zappepcs ( 820751 ) on Wednesday November 28, 2007 @05:10PM (#21509823) Journal
    turn out like a bad nightmare after watching A clockwork Orange ??
  • by mfh ( 56 )
    Now I'll find that sweet looking woman I saw at the bar back in 1993. I know she's out there somewhere... I just HAVE TO CONCENTR- oh no.
  • by algorithmagic ( 1194567 ) on Wednesday November 28, 2007 @05:14PM (#21509865)
    I worked in visual brain research for years, and can vouch there are lots of skeletons in the closet, or elephants in the drawing room: there is no accepted model of the statistics of real images (corners, occlusion, shading), nor of the algorithms necessary to infer them from inputs, nor of the learning process to infer those algorithms. Yes the brain is parallel, and yes it involves robust, fuzzy processing and analog values, but we not only don't know how the brain does it, we don't even know what problem it's trying to solve. The good news is that if this student does indeed have a business model and a real-world problem people will pay to solve, then the ratchet of engineering evolution could give us some real traction into understanding and solving this mystery. Good luck!
    • I seem to remember reading something about the visual heuristics the brain uses to identify faces and objects and so forth. There's some we do know, but I think you're right in that there is a LOT of information about how the brain works in this area than we don't know. Of course, we've only had what knowledge we do have (or at least think we have) about the brain for a relatively short time. The study of human brain is relatively young compared to the study of other parts of the body -- one of the main
    • by lawpoop ( 604919 )
      I remember reading somewhere along the line about a 'geon' theory of vision. This theory posited that the mind had a 'virtual reality' of basic 3-d geometric shapes, which the mind used like legos to build a model of what it saw. So you have cubes, cylinders, and spheres, which you used to model the things you saw.

      Then it occurred to me that very few things we saw were geometric objects, or composed of geometric primitives. It's really only until you start living in cities and dealing with manufacturing
    • by 12357bd ( 686909 )

      Yes

      The same goes for statistical classifiers. Human categories ( 'faces', 'cars' , 'landscapes' ) are not mathematical objects (there's no mapping between concepts/cultural constructs and formulaes/formal expressions). Any formal system trying to express a non formal one is doomed to fail, except for the very few special cases where human categories maps well defined mathematical objects (ie, ball - 2d/3dcircle, box-2d/3drectangle).

      Statistical systems try to create a map between basic data characteristics

  • by butterwise ( 862336 ) <butterwise AT gmail> on Wednesday November 28, 2007 @05:18PM (#21509933)
    You might end up with a search engine that just looks for pr0n.
  • You still need to physically tell it somehow what you are looking for. How useful would it be?
  • Anybody else think image-in-results-out when they first read the summary? Actually, even TFA doesn't make this plainly obvious until you're decently through it.

    Once I was past that, I thought it was pretty interesting. It could lead to more honest tagging of videos on YouTube, for example. No more keyword nonsense, just tags assigned by the engine.
  • This is a pretty useless article. Doesn't really tell how he's planning on doing it. It's a patent pending method. All it basically says is "Hey, look what we might be able to do". Even the quote from the expert doesn't do anything to tell me this problem is on its way to being solved.
    • Oh, I can tell you right now what he's planning to do with it. He's planning to sell it to Google.
      • It ever happen to anyone else where in the couple seconds between when you click the submit button and when the page refreshes, you see clearly what the person you are responding to actually wrote and you realize that you read it completely wrong?
      • I'm having nightmare images of the next generation of Google image search.

        It would be powered by dark room after dark room of people strapped into chairs, fed by IV, wearing helmets full of electrodes spearing into their brain. 24 hours a day, 7 days a week, these helmets send dozens of images into those poor, fried brains and sees if any of those over-saturated neurons picks up on a match. Then, Google posts results.
      • I doubt they're interested in this sort of thing right now. I submitted a paper on how to do multimedia similarity search to them when interviewing there, and was told that similarity-based image search isn't an area they're concerned with at the moment. Because it isn't, it's probably a better idea for him to go into it on his own (also, once they see it in action, they might want it).

        Also, everyone in computer graphics has some sort of image similarity search method, and I don't see anything particularl

    • Re: (Score:1, Insightful)

      by Anonymous Coward
      It's called vaporware. The research might work out beautifully someday, but apparently hasn't yet. Writing it up as news is probably a little premature.
    • Re: (Score:3, Informative)

      This is a pretty useless article. Doesn't really tell how he's planning on doing it.

      .

      I absolutely agree with you. Even the Computerworld (admittedly not the pinnacle of scientific reporting) article starts by saying "University of Ottawa student Kris Woodbeck is combining the neural processes we use to understand image data with the features of graphics processors." I don't even know where to begin with that statement. So he's come up with a model of neural image processing (a feat in itself)...and is map

  • Now I'll have to find someplace else to hide my twisted fantasies.
  • ..processors do one thing at a time, so they would be linear, not parallel.
  • it's impossible to tell if this guy is patenting the idea of doing vision on gpus (in which case there's prior art going back to before 2004 and probably even beyond that in the gpgpu community) or if he's talking about some tremendously clever collection of algorithms that happens to map well to gpu hardware. either way, i suspect that the poor guy is about to discover the hard way just how extraordinarily difficult this problem is.
  • all hype? (Score:5, Insightful)

    by snarkh ( 118018 ) on Wednesday November 28, 2007 @06:04PM (#21510585)

    Web search does not immediately reveal any details of his algorithm or any relevant papers, just media publicity. He does not even seem to have a web page.
  • light blain...

    Yeh, there be parrallellism there....

    (2 Ls up there, 2 Ls down here; 2R, 2L, 2L... get it?)
  • 'The brain is very parallel. There's lots of things going on at once,'

    I have a bit of an issue with that statement. I guess in a way it is true that the brain does multiple things simultaneously such as balancing the body and chewing gum ;), but any article [apa.org] on multitasking [cnn.com]will tend to point out that the brain isn't very good at processing higher functions simultaneously. I guess the main goal may not be to simultaneously process multiple images, but to quickly process a single image (which the brain is g

    • by Hatta ( 162192 )
      The brain can only do one task at a time, but it does this task by breaking it down into smaller tasks which are done in parallel.
    • You are confusing 'brain' with 'mind'.

      The mind has problems multitasking - not too different from a CPU. The brain does a lot of things in parallel. In fact, each neuron is independently doing it's own thing, muh like each transistor in a CPU...

      T

  • by Kazoo the Clown ( 644526 ) on Wednesday November 28, 2007 @07:53PM (#21511973)
    If you can, the patent system is more than a little bit broken, though I guess we all know that by now. I would think that the existance of the brain would constitute prior art...
    • There's prior art to mapping the brain onto electronic computing devices:

      It was done in at least one episode of Star Trek.

      And if future prior art published in the distant past is not suitable, then Wallace's cross human-rabbit brain mapping ("Wallace & Gromit - The Curse of the Were-Rabbit") might apply (a rabbit's brain IS a kind of electronic computing device, as is a human brain.

      Both examples are both "prior" and "art"!

      If not applicable, prepare to either pay a licensing fee or stop using your brain
  • Crap article - and it sounds as if this fellow should put in a resume to Evolved Machines - http://www.evolvedmachines.com/ [evolvedmachines.com]

    An Nvidia spot....*drum roll*....featuring neural simulations on GPUs
    http://www.nvidia.com/object/tesla_testimonials.html [nvidia.com]
  • This isn't a terribly new idea. [vt.edu] Just a lot of hype. Boy, I wish my Ph.D. dissertation work got Slashdotted!
  • While I was an intern at the Jet Propulsion Laboratory, back when I was an undergraduate, I was very gung-ho about biologically inspired computing - I implemented an automatic flowchart positioning system using a genetic algorithm that would "evolve" a correct solution to the problem. While this certainly worked to some extent, the instability and sheer unpredictable nature of using such a stochastic algorithm made it impossible to use in a mission-critical setting. Many biologically inspired algorithms sol
    • by 12357bd ( 686909 )
      One of the most interesting works in this field was Dynamic synapse for signal processing in neural networks [freepatentsonline.com], unfortunatelly that was 2002!
    • by mcoletti ( 367 )

      the tremendous success that is evolution on this planet has overshadowed its inherent weaknesses - that it is a greedy, local optimizer which cannot reach a large amount of the possible biological search space due to being stuck in local optima

      Untrue. There are EC mechanisms to deal with inferior local optima such as hypermutation, restarts, coevolution, island models, and dynamic population sizes, among others.

      verything must be constructed out of self-replicating units (these two factors are why something

      • the tremendous success that is evolution on this planet has overshadowed its inherent weaknesses - that it is a greedy, local optimizer which cannot reach a large amount of the possible biological search space due to being stuck in local optima

        Untrue. There are EC mechanisms to deal with inferior local optima such as hypermutation, restarts, coevolution, island models, and dynamic population sizes, among others.

        The purpose of my statement was not to suggest that EC is hopelessly flawed, but that biologi


  •     I'd imagine that the number of "Probable Hits" will be heavily weighted toward pr0n sites if anyone from around here gets mapped.
  • I call BS on the article as well...

    As far as "generic object recognition" goes, we are VERY far from a Holy Grail. State-of-the-art algorithms so far have a 45-55% successfull recognition rate, when dealing with only 101 objects categories (Caltech 101 database). Basically, with only 101 object to choose from, your "search engine" would get it wrong half the time. Not very useful if you ask me. Let alone with hundred of thousands of categories as he claims.

    On top of that, the best and brightest are alr

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