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Interwoven Patents Some Aspects Of Image Search
prostoalex writes "InterWoven patented locating and identifying image content via shapes, texture, color or resemblance to another image. No official word yet on whether the company thinks there are any infringers."
Google doesn't look at the image, just the filename, alt tag and surrounding context. Likewise with Ditto. I fail to see how that involves "shapes, texture, color or resemblance to another image". There are other companies out there that should be worried, but the ones you mention are about as far from that patent as you can get and still search on images.
These guys are a closer match, but since they are doing 3D CAD/CAM models, perhaps they are safe to.
On the other hand... these guys (eVe Image Search Toolkit) could be in trouble if they are not the patent holders themselves.
This patent seems more applicable to finding images that have similar color properties and gross image shape, which could be really useful when looking for images that go well together when compositing, not for finding pictures of a specific thing (unless you have an example that is very similar to the object you seek.)
So for the forseeable future, metadata will be far more successfull at finding images. Computer vision is still incredibly primitive: more so than computer speech recognition ten years ago.
Sig under construction since 1998.
that for the next twenty years no one will be able to search for an image based on those sorts of similarities without money going to these people? TANJ.
The World Wide Web is dying. Soon, we shall have only the Internet.
About a year ago it occured to me that this concept would be patentable. Of course, I had neither the time, inclination or business plan to follow up on it.
"Eve of Destruction", it's not just for old hippies anymore...
I believe Google just uses surrounding textual metadata from the web page to identify a likely candidate image... combined with a false positive approach where an image named or labeled money.gif on a page with 50% content about puppies.. probably the image isn't a puppy, while all other large file sized images most likely are puppies...
A fool throws a stone into a well and a thousand sages can not remove it.
I'm not one to suggest violence but at the rate the patent office is going we Americans might have to walk up to the front door, kick it in, and beat some F%&*#&% sense into those people.
-=[ Who Is John Galt? ]=-
Honestly, if this company has an implementation of this system that works reasonably well, they deserve a patent on it. Extracting shape/texture information into (I'd assume) feature vectors effectively isn't the kind of trivial "development" that a system that performs different functions depending on how long a button is held down is.
However, if all they are patenting/developing is the searching, they're douchebags. I say this because after you have the feature vectors, the next step is a Nearest Neighbor Search, and there are already a number of algorithms for determining nearest neighbors. Unless their method somehow gets around the "curse of dimensionality", or provides other major improvements, I will be unimpressed.
I have discovered a truly remarkable sig which this margin is too small to contain.
The patent is more concerned with the method of converting the image into a manageable dataset that can be searched. So, it does not seem to rely on feature vectors at all. Moreover, this does look different than approaches I've seen to do the same thing. Fractal compression of images isn't terribly new, it's covered a bit in "Chaos and Fractals: New Frontiers in Science." However, I am not familiar with this method of classifying images based upon results from such a technique, this may very well be a novel development... dare I say, even worthy of a patent?
I have discovered a truly remarkable sig which this margin is too small to contain.
... but some of the more interesting stuff happened more recently (but still awhile ago). I have recently been looking at Fast Multiresolution Image Querying as a means to find similar images for f-spot. But it sounds like this patent is very broad and generalized, and systems like those described existed long before the patent. In fact, the paper linked above describes some of those systems.
GMail invites for completed freeipods.com of
It sounds like this kind of search/recognition mechanism could be used for content filtering. For instance, at a library, a kid searches for content using GIS, the boobie-recognized images could be filtered. I wonder how well that would work...
How can some one patent the idea of searching for images. You can patent an specific implementation, that I agree/live with.
Ok if you had patented a certain algorithme and someone else was using it. I would agree to sue them. Just because you made a way to search for images and I later found another way with the same results doesn't mean I copied you.
This way of patenting sounds like me in the stone age patenting a vehicle (which means basically anything) which doesn't depend on animal power.
If this system of patenting is legal. Then hereby I patent a way of travel to the stars using an engine thats able to exceed the speed of light. Please deposit all money on my paypal account. Thank you very much. (idiots, no not you but the legal system)
-- I don't buy it, I grow it.
Based on a short read of the article and the patent, I think that my former company (Audre, Inc., now eXtr@ct and Carnegie Mellon's Robotics Institute, among others, produced prior art as far back as the middle 1980's, back in the day before software and algorithms were patentable. I would go so far to say, at least at first glance, that some of the claims are superceded by convolution hardware dating to the 1960's at GE.
GE generated X:Y location & degree-of-match for an image regarding each of a set of simple image filters (rings of various radii and angular slits at 2 degree separation). This data was then cross correlated (some experiments used early neural nets, IIRC). They were successful at finding different types of features in aerial photography, such as farm, urban, water, grass, and forest.
The Audre Entity Recognition system used, among other things, input from a convolution/correlation system and a variety of other feature extraction methods, and used various means to build feature models from scanned engineering drawings, contour maps and other large format images. The system could produce a complete 3D terrain model from a simple contour map. The Visual Understanding Lab at CMU with which we worked also worked on using color features, more than Audre did. We even explored X-ray images, but scanning hardware of the time didn't have sufficient reliable gray scale capability.
A company in Denver or thereabouts was building systems using fractal decomposition of images as the fundamental data model for both display and recognition. They used a hexagonal cell model rather than the common rectangular one.
The patent is written in "patentese", so it'll take some study before I can be sure.
[Easter Egg: Check these movies (1, 2) and animated gif of ray tracing at 0.99c, by R. Thibadeau at CMU.]
It's easier to be a result of the past, but more fun to be a cause of the future! http://www.spacefinancegroup.com/
Ummm, there is a whole subfield called "content-based image retrieval" that has been doing this for over a decade. See for example, http://www-student.informatik.uni-bonn.de/~gerdes/ CBIR/
for a nice survey containing 39 examples of prior art!!!! Perhaps IBM would like to comment on the patent (see their QBIC system).
Hey, the next time anyone comes up with a brilliant idea that they don't have the time to develop into a business, why don't they patent it and release it to the general public? That would ensure the freedom of simple systems like this--which is almost as old as dirt. (Humans have been doing it as long as we've existed, after all, and we weren't the first.)