New Object Recognition Algorithm Learns On the Fly 100
Zothecula writes "Scientists at Brigham Young University (BYU) have developed an algorithm that can accurately identify objects in images or videos and can learn to recognize new objects on its own. Although other object recognition systems exist, the Evolution-Constructed Features algorithm is notable in that it decides for itself what features of an object are significant for identifying the object and is able to learn new objects without human intervention."
I could be wrong... (Score:3, Insightful)
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The big news here is that it's being trained to detect bullshit. It's currently 0-10.
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And it has figured out that all objects have been constructed from an all knowing being. Divine intervention if you will.
http://aims.byu.edu/mission_statement [byu.edu]
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With our algorithm, we give it a set of images and let the computer decide which features are important.
Without seeing their code that is my
Re:I could be wrong... (Score:5, Interesting)
The way I understand it is that it identifies recurrent features and learns them. Meaning that giving it a huge image library with no labels would mean it can recognize say, roses, but it would call them "object 193131", not "rose".
Re:I could be wrong... (Score:5, Funny)
Well, you know what they say... "a rose by any other name would posess eigenvalues closely matching those of object 193131."
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But how is that different from current AI?
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But how is that different from current AI?
Current AI would call it "object 0x2f26b".
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You are full of 483027!
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Re:I could be wrong... (Score:4, Insightful)
Sitting on a street, a "bicycle" is an object because it is most like to be operated on as a unit. But to a bicycle mechanic, a bicycle is a collection of objects, such as a frame, a seat.. and so on because they need to decompose the "bicycle" construct to do their job. To somebody on an assembly line putting together bicycle seats, a seat is (at least initially) several different objects.
So, truly unsupervised algorithms cannot do useful recognition - that is, classify objects the same way people do. (A robot that could experiment with its environment and learn to use "objects" could come closer).
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That's an overly narrow defintion of "useful recognition".
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The unsupervised algorithm discussed in the article seems to code some sort of visual input and, I'd infer, to perform clustering, which permits it to assign labels (i.e. let's say, 'tree', 'human', etc.) to objects it has encountered. It can use this schema which it has constructed to assign objects it hasn't seen before to a cluster - that is, it labels novel inputs in accordance with its schema. Thus, the algorithm 'recognizes' classes of objects. I'd imagine if you granularize the detail level of detail
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Your logic is flawed.
By splitting object-recognition into two cases... ... you have not proven that algorithms cannot perform object-recognition. You still need to show that one of the cases cannot be performed by an algorithm. As case A is trivial, and case B is what this algorithm does your argument falls apart. Collections of shapes can be recognised by probability of occurrence. There is no need for interactivity, simply enough video
A: Atomic shapes
B: Collections of shapes
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With regards to training, It is possible to perform this learning task without direct supervised (tagged data) training.
Imagine the following:
Take a trillions of images from the web, and use unsupervised, clustering methods to group images into groups of equivalence, given that you have great features that allow you to do that.
Then,
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This can't be far off, I read a paper a while ago (still trying to find it, this post is a bit redundant without it) which would "detect" the capital of a country from how often they were found in text together. (Probably pre-loaded with country names, this would just have the image as the needle)
I'm sure "Object 1387" and "Nyan cat" will soon be matched :)
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I am not a programmer so could someone explain to me how that is different?
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But that is exactly what people do. Other than a few hard-wired patterns (e.g. faces), we "learn" to recognize objects by being exposed to multiple examples of those objects and told the label to apply to them.
Though the argument could be made that people don't learn on their own either...
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Perhaps the news is that someone from Utah accepts the principles of evolution?
He taught them to machines because he didn't manage to teach them to the people around him.
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Perhaps the news is that someone from Utah accepts the principles of evolution?
That's cute and all. But my brother, who is a devout Mormon, got an MS in evolutionary biology. At BYU.
Bah ... (Score:2)
Let it loose at the Adult Entertainment Expo [huffingtonpost.com].
If it can figure out what half of that stuff is, it's a brilliant algorithm.
If not, it will probably be hilarious to see the results.
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If not, it will probably be hilarious to see the results.
Let me check...BYU...sex toys...yes, it probably would!
Comment removed (Score:3)
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Like I've said in the past, mankind simply can't seem to stop itself from building Skynet piecemeal. Too dumb and trusting to think all those interesting things could ever be made into weapons or instruments of control.
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Governments are already building them into weapons. The question is, are we going to have the same arsenal? All this tech is coming, we can't just stick our heads in the sand and hope for sane competent leadership when it does arrive.
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But we can demand technology kill switches.
Just as security was bolted onto the internet to make up for the lack of it being designed in, we shouldn't find ourselves in a position of having to bolt security onto our televisions, cars, and robotic servants.
This particular algorithm has a lot of uses. We'd want that garbage sorting automaton to the entire system stop dead in its tracks when a human hand came through in the stream of cans and bottles and waste paper being dumped into the maw of a waste sorting
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Evolution at BYU (Score:1)
At least there's one professor at BYU that believes in evolution!
Re:Evolution at BYU (Score:5, Informative)
At least there's one professor at BYU that believes in evolution!
I understand why it might be tempting to put BYU in a basket along with the rest of the evangelical christian universities. However, on the issue of evolution it could not be more different. I graduated from there with a degree in microbiology and my college at least evolution was the coin of the realm, just like it is in any serious biology department. I did not have a single professor that did not see evolution as you might expect a biologist to see it; as the only serious explanation of the data at hand, the only theory that works with what we know and provides valid predictions of future results. Not once did I hear even the smallest bit of credibility being given to creationism or its various variants (intelligent design, etc).
And yes, my professors were all Mormons. You might ask yourself how they square this. It turns out that while there are certainly Mormons that take a very literal reading of the bible on this issue, that is not the official church position, and there are many members that don't see it that way at all. Basically I had several professors that explained it as religion was about how to live life, science was about how life works, and we really have no idea how the two come together. The bible, while providing a lot of information to believers on a moral life, provides no real information on how the world works in any of the scientific fields.
Interestingly, many believe this is on purpose, that God has no interest in proving his existence; it's a matter of faith for a reason. Because of this He stays out of offering scientific explanations. I realize that sounds distinctly like a cope-out, but frankly it leads to a fairly rational place where you can function as a scientist an still be a Mormon. And by function I don't mean some half-way hands over eyes sort of a way, but in a real, go where the evidence takes you sort of a way.
Take it for what it's worth, but that was my experience
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I laughed every time he had to make a disclaimer
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I suppose this depends on a number of things, and perhaps in the end you may be right. But at the moment there really isn't a clear conflict; the conflict is more manufactured than real, especially if you see religion as a road to life happiness and not an explanation of all things. I admit that there is a certain about of dealing with ambiguity that is required. Frankly, I tend to be much more of an agnostic or a deist than your average Christian. I tend to believe that my life is mine to live, there i
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So you, personally, have performed every experiment ever done? Or are you trusting (having faith) that somebody a bit smarter and/or with more resources than you has done so and not lied to you?
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On the fly, but.... (Score:4, Insightful)
Does it work in real time? I can't find any more information than marketing buzz in the article (and the BYU article)...
Is there a paper or anything with a bit more [technical] detail?
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Here's the journal article:
http://www.sciencedirect.com/science/article/pii/S0031320313002549 [sciencedirect.com]
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Academic journals traditionally require the authors to assign the copyright to the publisher. The authors do not get paid directly, but publications are an important factor in tenure decisions and general academic prestige--"publish or perish."
Some journals allow the authors to post the paper on their website, and some journals which do not technically allow it have generally ignored it in the past, but some publishers have been cracking down on the practice recently. [borneonashhash2013.org]
Here's what I hope they get (Score:2)
Paper? (Score:3)
Anyone got a link to the actual paper?
I wonder if this can be used for image compression. Because if you know e.g. what a bicycle looks like, you don't have to compress it.
Re:Paper? (Score:4, Informative)
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Is this [sciencedirect.com] the one? It doesn't appear that the researchers have posted a manuscript, and I'm not sure that Elsevier would take kindly to it if they posted the published draft (although many researchers do so anyway). That, along with a lack of public interest in reading articles upon which pop science articles (like the one in the link) are based, probably explains the lack of a link or reference to the original article. If you have access to a library that subscribes to Pattern Recognition, you can get the ar
Not new (Score:1)
Nothing is performed on the fly. It's just another feature extraction and selection pipeline.
1) Deep Neural Networks also save the feature engineering step (for instance http://media.nips.cc/nipsbooks/nipspapers/paper_files/nips26/1210.pdf [media.nips.cc])
2) If as suggested by the title you are interested by on-the-fly object recognition, look at Tracking-Learning-Detection (TLD) (http://info.ee.surrey.ac.uk/Personal/Z.Kalal/tld.html)
Hope it will not fail Tranny or Female test (Score:1)
Hope it will not fail "Tranny or Female" test
On the fly? (Score:2)
New object recognition algorithm learns on the fly
I know wearable computing is the next big thing but putting one there - especially if it has a camera attached - is going to look a little bit... weird.
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No, they are making very small devices you'll not notice on the fly. And they'll add circuits to control the fly. The result will be a biological espionage drone which nobody will suspect.
However people will try to kill it anyway.
*Sigh* (Score:4, Interesting)
notable in that it decides for itself what features of an object are significant for identifying the object and is able to learn new objects without human intervention
For Christ's sake. The AdaBoost face-detection algorithm - the one that everyone uses today - does precisely this, and was developed in the the 90's.
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...that's right, the the 90's...
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Indeed. My issue was with the poor reporting, not with the actual research.
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No, all its knowledge about what constitutes a face is learned.
There's a 'training' process, where the algorithm is fed a set of images of faces and another set of non-face images, and from there the algorithm determines what features it should be looking for to determine face from non-face.
AdaBoost does face detection (is this a face?), not recognition (whose face is this?), however, so it's not quite as impressive as the algorithm in TFA, which is able to recognise lots of different types of objects.
PDF or it did not happen (Score:4, Insightful)
Why should I get excited about something written by a journalist where there must be something writeen by scientists? Where is the PDF of the scientific paper to download?
What is the novelty of this algorithm? (Score:1)
First of all, is this the right paper [sciencedirect.com]?
It seems that the topic of the linked article is a new unsupervised [wikipedia.org] algorithm that categorizes images. The linked article says that 'the Evolution-Constructed Features algorithm is notable in that it decides for itself what features of an object are significant for identifying the object', which unsupervised algorithms do implicitly, no? It is also stated that the algorithm 'is able to learn new objects without human intervention' - so if I'm interpreting this and the a
actual link to paper (Score:3, Informative)
team,
fyi: http://contentdm.lib.byu.edu/utils/getfile/collection/ETD/id/3021/filename/503.pdf
-me
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Need better examples (Score:1)
Perhaps if this was explained in terms of an example whereby you describe how existing AI uses or learns the training set and how the newfangled way does it different.
Sounds like NEIL (Score:2)
This sounds a lot like the Never Ending Image Learner project: http://www.neil-kb.com/ [neil-kb.com] which is crawling the web and trying to extract visual knowledge.
Mild Sensationalism (Score:1)