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Hitachi Develops New Visual Search

Tech.Luver writes to tell us that Hitachi has developed a new visual search engine that can supposedly find similar images from within millions of video and picture data entries in around 1 second. "The technology assesses the similarity of images based on image characteristics presented as high-dimensional numeric information. The information is acquired by automatically detecting information regarding the images, such as color distribution and shapes."

9 of 166 comments (clear)

  1. Hmmm.... robotics? by fyngyrz · · Score: 5, Interesting

    This is interesting to me - if it performs well - because this is one of the key missing elements for robotics; robots have a lot of trouble trying to match the environment around them to stored records of objects unless the environment is severely constrained. I'm not speaking of AI here (or at least, not yet) but just robots that would be able to clean your floor, carry your groceries, navigate in a burning building, walk your dog, tend your lawn. If they can classify images against stored images well, we're that much closer to generally useful and at least semi-autonomous robot devices.

    Training might be a little annoying the first few times, but once you had a good database, you could replicate - or share via RF, that'd be freaky... neighbor's robot learns what a ferret looks like, now yours knows too - so that newer models were more and more informed right out of the box. Crate. Coffin. Whatever.

    Add an associative database so that images normally found near other images which have just been found are searched first, and perhaps you could get the general search time down from the quoted 1 second, I'm thinking. One second is kind of pokey for a lot of robotic applications. But if the thing is in a kitchen, why would it need to be looking to recognize images that are found in a shipyard?

    And I, for one, would welcome our semi-autonomous, environment recognizing, floor cleaning robot underlings.

    --
    I've fallen off your lawn, and I can't get up.
    1. Re:Hmmm.... robotics? by lawpoop · · Score: 4, Interesting

      I'm not speaking of AI here (or at least, not yet) but just robots that would be able to clean your floor, carry your groceries... Well, you are talking about AI here. It turns out that it's relatively easy to make a computer that can beat humans in chess or do complex math equations, but something as simple as walking with 6, 4, or two legs, which a lot of really stupid organisms do, is really difficult. Something like distinguishing 'indoors' from 'outdoors' or a cloud bank from the bushes, seems way in the future.

      My pet theory is that we don't have the right kind of device yet. A mind, the 'function' of an organic nervous system, is not a Turing machine. I don't really understand the math behind it, but Goedel's incompleteness theorem seems to show that a human mathematician can understand certain mathematical proofs that a Turing machine can never prove. Since all computers are a essentially a Turing machine, no matter how fast or parallelized they are, or how much memory they have, they will never be able to do what a human mind can do. So, maybe someday we will have artificial intelligence, or, a floor-washing robot, but we currently don't have the right kind of device that can do it.
      --
      Computers are useless. They can only give you answers.
      -- Pablo Picasso
    2. Re:Hmmm.... robotics? by kebes · · Score: 3, Interesting

      Your implication is that the human mind cannot be reduced to a Turing machine. I am in the other camp--who believe that the mind is subject to rigorous physical law, and that physical law can be expressed arithmetically (in principle), and so the human mind is a Turing machine.

      Godel's theorem says that a consistent arithmetic system will contain unprovable truths. Put otherwise, such a system cannot be both consistent and complete. Thus the Godel counterargument to Strong AI (that human minds and computers are not fundamentally different) is that humans (e.g. mathematicians) can prove things like Godel's theorem, so we are able to "rise above" the arithmetic and exist in states of full proof and full consistency.

      But I think there is a flaw in that logic (note: I am not a mathematician). The theorem doesn't preclude that a given arithmetic system (e.g. human mind) will be able to prove a truth that a weaker system ignored. Thus our ability to see certain truths doesn't mean that there are not other truths that are unprovable to us.

      More fundamentally, no one has actually shown that the human mind is either consistent or complete (proving both would be required to show that we are not subject to Godel's theorem). The human mind is a computational device evolved to solve real-world problems, like escaping predators, rather than contrived ones, like mathematical proofs. It is thus in fact likely to be an inconsistent (internally contradictory) computational system. The human mind may be incomplete and inconsistent.

      I agree that "true AI" will require vastly more computer power, and much more sophisticated algorithms than we have today. But the emerging evidence, from what I've seen, is that "true AI" can be achieved, at least in principle, by a Turing machine.

    3. Re:Hmmm.... robotics? by lawpoop · · Score: 3, Insightful

      Your implication is that the human mind cannot be reduced to a Turing machine. I am in the other camp--who believe that the mind is subject to rigorous physical law, and that physical law can be expressed arithmetically (in principle), and so the human mind is a Turing machine.

      I'm not saying that the mind is not subject to physical law, or is not based on math. All I'm saying is that the mind is not a Turing machine ( though it probably would have to have a Turing machine in it somewhere ). It's a different *kind* of machine, not a super-powerful Turing machine.

      Goedel basically showed that a Turing machine cannot do *all* the kinds of math that a human mind can do ( though it can do some). Not that a Turing machine lacks a certain amount of power, but just that it never will. It's just quantitavely the wrong tool for the job. It doesn't matter how much power you give it; the 'weakest' Turing machine is essentially the same as the 'strongest' one; it just simply can't do certain things. If a human is able to perceive and understand this, to know something that a Turing machine can't know, then the mind cannot *solely* be a Turing machine. This does not mean that the mind is not a different *kind* of machine, based on physical law, instead of some mystic hocus-pocus; it's just that it's not a Turing machine. My claim is that the mind is a qualitatively different kind of machine, not a Turing machine.

      Goedel's theorem says that a consistent arithmetic system will contain unprovable truths. Put otherwise, such a system cannot be both consistent and complete. Thus the Goedel counterargument to Strong AI (that human minds and computers are not fundamentally different) is that humans (e.g. mathematicians) can prove things like Godel's theorem, so we are able to "rise above" the arithmetic and exist in states of full proof and full consistency.

      But I think there is a flaw in that logic (note: I am not a mathematician). The theorem doesn't preclude that a given arithmetic system (e.g. human mind) will be able to prove a truth that a weaker system ignored. Thus our ability to see certain truths doesn't mean that there are not other truths that are unprovable to us.

      I don't think the implication of Goedel's theorem shows that we 'rise above' the Turing machine, but rather that we have a qualitatively different awareness or knowledge that a Turing machine doesn't have.

      Goedel's theorem is recursive. Any human mathematician can see that no matter how powerful the symbolic system is, the Turing machine will never be complete; there will be truths that the system can't prove. No matter how much you expand a particular system to show any truth a weaker system missed, there will be more truths that the newer, more powerful system missed. This process can go on ad naseum into infinity. A human mind can perceive this foray into eternity, but the Turing machine has no way of proving it. How could a human mind perceive something that a Turing machine couldn't, unless we had some component that was fundamentally different than a Turing machine?

      What we seem to have that the Turing machine doesn't is meta-knowledge. We can see that any attempt to create a complete and consistent arithmetic system on a Turing machine will just lead to an endless series of more powerful systems that produce ever more elusive truths, and the process never ends. In this sense the Turing machine is 'myopic' -- it will never stop and say "Hey, I'm not getting anywhere with this; this is an infinite loop. No matter how powerful the system is, there will always be more truths that it cannot express." It's unable to know what it can't know, so to speak. However, as humans, we can somehow see the 'big picture', that no matter how powerful a system you make, there will always be another level of truths out there.

      More fundamentally, no one has actually shown that the human mind is either consistent or complete (proving both would be required to sh

      --
      Computers are useless. They can only give you answers.
      -- Pablo Picasso
    4. Re:Hmmm.... robotics? by aragszxki · · Score: 3, Informative

      Gödel's theorems have nothing to do with representing the human mind in any form. They cannot be applied to the human mind for the purposes of answering the question of strong AI. Basically, the only thing that Gödel's theorems do is carry the Liar's Paradox ("This sentence is false.") to the level of basic arithmetic. There is no magical process that proves or disproves anything about the human mind. The confusion stems from the fact that the mathematical terms "incomplete" and "inconsistent" seem to imply so much more when quoted in a non-mathematical context.

      For anyone who is interested in reading further, Gödel's Theorem: An Incomplete Guide to Its Use and Abuse contains a thorough discussion of the issue.

      I would like to believe that we will achieve strong AI one day. However, referencing Gödel's incompleteness theorems just because they sound appropriate at first glance does not give any argument scientific credibility.

    5. Re:Hmmm.... robotics? by mikael · · Score: 4, Interesting

      To implement a visual search engine you need to be able to perform the following:

      texture segmentation - splitting up a picture into segments of distinct objects. In a panoramic scene, you want to split the picture up into objects such as sky, ocean, waves, beach, boats, pier, wall, people, animals. As a psychological experiment, you can show someone a picture , point to a particular point and ask them what the first word that the associate with that point is. Then you will see how every scene becomes segmented by our own vision systems.

      Basic image segmentation is implemented using edge detection by Fourier Transforms (FFT, IFFT, DFT). This is a very computation intensive stage that is typically implemented using DSP's, GPU's or even dedicated ASIC's. Data used by the FFT can be in any dimension 1D (audio/radar), 2D (images) and 3D (volume visualisation). But to match the resolution of a human eye, you would need a 100 Megapixel floating point framebuffer.

      texture classification - having identified the silhouette of an object, now attempt to match the contents to a particular object. Simple ways include colour histograms and silhouette matching. More advanced methods attempt to simulate the first few layers of the human retina using Gabor filters, Ring filters and Wedge filters.
      But just to model a single type of retinal cell requires one or more FFT operations for an entire image. And
      there are at least twelve different types of such cells. For efficiency precalculated results of sample images are generated (these are referred to as feature vectors) and then compared against the results of any new image.
      For a really technical explanation of how human vision works have a look at The organisation of the retina and visual system

      texture retrieval - the actual design of the search engine to retrieve images through content rather than just keyword:

      QBIC - Query By Image Content. IBM's image retrieval database system

      All of this has to performed for a single image. For an entire movie requires the processing of hundreds of thousands of images.

      --
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  2. pr0n by tronicum · · Score: 4, Insightful

    great! new way to find even more porn.

  3. Will Google copy or buy this technology? by bepolite · · Score: 3, Interesting

    I would think this would be a big and useful upgrade for http://images.google.com/

    --
    Always be polite.
  4. Since when can an ancient indian tribe ... by SengirV · · Score: 4, Funny

    ... long since forgotten, be responsible for such innovative technology?

    --

    Prof. Farnsworth - "Oh a lesson in not changing history from Mr I'm-My-Own-Grandpa!"