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Computers Outperform Humans at Recognizing Faces
seven of five writes "According to the recent Face Recognition Grand Challenge, The match up of face-recognition algorithms showed that machine recognition of human individuals has improved tenfold since 2002 and a hundredfold since 1995. 'Among other advantages, 3-D facial recognition identifies individuals by exploiting distinctive features of a human face's surface--for instance, the curves of the eye sockets, nose, and chin, which are where tissue and bone are most apparent and which don't change over time. Furthermore, Phillips says, "changes in illumination have adversely affected face-recognition performance from still images. But the shape of a face isn't affected by changes in illumination." Hence, 3-D face recognition might even be used in near-dark conditions.'"
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computers outperform humans on math equations
-Dipster
It's really annoying how much of this research never gets turned into product.. or, worse yet, it gets embedded in some proprietary piece of shit hardware instead of being released as a reusable component. I'd love to add some good facial recognition to my pet robot, but I'm not buying your watt sucking camera.
How we know is more important than what we know.
I wonder whether these scientists lose any sleep over how their research advances will contribute to the future of our societies.
once the technology becomes more refined, they could put a camera connected to a computer(stored with all the mugshots in the nation) near a bank or other commonly visited area be able to catch tons of criminals
When a human makes a mistake recognizing a face, they suffer the results. If that's identifying a criminal, they can be cross-examined, or even sued or jailed, depending on what they said that face did.
When computers mis-ID a face, do we cross-examine and maybe punish its programmers?
--
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My tinfoil hat has a visor.
I, for one, welcome our face-recognizing overlords...
"Nature bats last..."
if(hot_gurl) {
RingBell();
}
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How good are computers at recognizing a face after ten or twenty years? I doubt the algorithms can recognize, say, a teenager based on photos taken prior to puberty. Also, can they maintain accuracy even if somebody has a new scar or puts on dark sunglasses? How much of a face does it take to make a match?
so, apparently, plastic surgery doesn't exist.
"for instance, the curves of the eye sockets, nose, and chin, which are where tissue and bone are most apparent and which don't change over time."
Geez.
How we know is more important than what we know.
It's a question of time 'till there 's a law that forbids to wear anything that partially covers your face in certain public areas.
I think I have about ten years 'till computers are able to interpret my front-head as a 'face' so I'm safe.
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Human face recognition is run by a several hardwired circuits operating in parallel (ie. fast, with little control) with the results put together after by some heuristics -- a good enough guess. What humans need to get from facial recognition, and what their ancestors required and so developed through evolution, is nowhere near the same thing facial recognition software is after. Humans need to recognize quickly that there is a face and what information it's displaying far more than they need to differentiate one from another. Facial recognition software does just the opposite. Also, the software does the complete job every time. Humans only process as much as they need to in any given instance.
If "better" is based on the standards of humans (fastest good enough guess) rather than machines (as correct as possible, complete & in depth), humans win.
"I may be synthetic, but I'm not stupid." -- Bishop 341-B
And I'm pretty sure the computer won't be able to recognize the face after the facial.
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Google seems to be deploying something similar
.A few years back (well, nearly a decade actually), I did my master's thesis in a lab that among other things did work on face recognition. The experts there assured me that perhaps in 50 years or so computers might be able to approach human face recognition capabilities. Apparently the development was far quicker than they could have imagined.
An interesting technical point is that in fact the algorithms haven't changed a lot since then - it's still mainly various adaptive systems such as neural networks and support vector machines. The really big breakthrough is in the data collection - in the sensors and scanners. What they couldn't imagine a decade ago was the type of accurate automatic 3d face modeling and measurements that can be done today. It's also how certain computing methods that were deemed unsuitable a few years ago are coming back big time (neural nets for instance). I guess the time wasn't ready for them the last time due to computing power and memory limitations (and of course sensors as in this case).
After LA the incident in May where protesters and cameramen kept running into police batons and shooting themselves with stolen police guns, the LAPD wants the city council to ban masks and goggles from public demonstrations. A law somewhere in Europe against masks was recently applied to burkas (no source, but google can backup any claim).
Go is not yet as well-automated as chess, but it appears that go-playing software is rapidly advancing:
t ml
"Two Hungarian scientists have now come up with an algorithm that helps computers pick the right move in Go, played by millions around the world, in which players must capture spaces by placing black and white marbles on a board in turn.
"On a nine by nine board we are not far from reaching the level of a professional Go player," said Levente Kocsis at the Hungarian Academy of Sciences' computing lab SZTAKI.
The 19 by 19 board which top players use is still hard for a machine, but the new method is promising because it makes better use of the growing power of computers than earlier Go software."
Link
See also:
http://zaphod.aml.sztaki.hu/papers/ecml06.pdf
http://citeseer.ist.psu.edu/vanderwerf03solving.h
http://www.primidi.com/2007/02/26.html
-kgj
-kgj
I'll be impressed when they can recognize caricatures as well as humans.
One of the academic research areas I've been involved in, is study of the so-called "Other Race Effect". There is some evidence that people have quantifiable error when asked to identify faces of people of other races than their own.
Computers won't be subject to this.
-fb Everything not expressly forbidden is now mandatory.
I always knew sometime in the future we'd be wearing those 80's wraparound sunglasses everywhere. That or one of those nifty 3-in-1 fake nose, mustache and glasses kits.
I'm researching 3D Face Reconstruction and Recognition for my PhD (see my website). The structured light scanner I use to acquire my 3D data takes less then 0.2ms for the 2 phase capture of structured light / texture images and then about 30 seconds to produce a high resolution model from the 4 stereo images. This is sufficiently fast to capture a subject even if they are moving during the capture process. Using this technology a subject must be suitably close to the cameras for the reconstruction to work, however, plenty of other techniques (such as model based reconstruction) allow 3D face models to be reconstructed using a single camera located quite a distance from the subject. In short 3D recognition is becoming the norm in the face recognition field as current 2D algorithms begin to reach their limits.
Because that's not what face recognition software was made for. When people watched John Cleese, they knew they watched a celebrity and they also knew that not too many celebrities would dress up like this and do the silly walk. Only using all this extra information made people recognize John Cleese. Chances are that even in a small town you'd find quite a few people who, if dressed up and walking like that, would easily pass as "John Cleese". On the other side most actors/models would not be recognized by anyone reliably if they don't have their make up and if lighting differs from the studio where they usually have their pictures taken.
Face recognition software on the other side doesn't make those assumptions but instead focusses on identifying people from a large population of registered images, using no extra knowledge and making no assumptions. All the face recognition vendor test says is if you put up 1000000 random faces, people would misidentify more of these faces as John Cleese than modern algorithms would.
These face recognition programs are fantastic!
http://photos-489.ak.facebook.com/photos-ak-sf2p/v 74/6/57/529971421/n529971421_97489_2572.jpg/