Face Recognition - Real or Science Fiction?

An anonymous reader writes "Facial recognition software has been touted as one of the technologies that will change our future, particularly in law enforcement. How close are we to being recognized by a computer anywhere we go, as portrayed in movies like Minority Report? According to the industry's recent Public Relations releases, these products are closer than we think. The reality though, is that current products work only when utilizing a small comparative sample, and any attempts for an individual to disguise themselves typically throw off the results. To see how far this technology needs to go before becoming mainstream, one site utilized Government-tested face recognition software, available freely through MyHeritage.com, to compare hundreds of famous people, animals, and cartoons to a database of 2,000 celebrities. Some of the results showed promise for the technology, but most were just funny — for example, who would mistake Barbara Streisand for Shrek, or Lance Bass of N'Sync for a Teletubby?"

Comments

trick question

[Lurker2288]

"who would mistake Barbara Streisand for Shrek, or Lance Bass of N'Sync for a Teletubby?"

I think it's more a question of 'how many beers' than of 'who.'

Re:trick question

[WindBourne]

Or what computer program, camera, and lighting that you have. And add facial hair (perhaps on all), cosmetics(again on all), or even haircuts. Basically, it will always fail on those that do not want to be recognized. But down the road(20 year), it will work well on those that are not suspecting it i.e. it will be a good way to track down regular citizens when the government is granted the power to grab whoever they want and attribute it to say terrorism. Fortunately, we are a long ways from that. Or are we?

I've heard this for years

[2.7182]

After working in computer vision for 5 years I've realized that most problems aren't hard - they are not well defined. Mathematically face recognition is not a problem that can be stated.

Many other problems in CV are like this - edge detection, segmentation, etc. But people write hacks that work in restricted conditions and say they've solved.

And look, you could always just put on those Groucho Marx glasses.

Re:I've heard this for years

[PieSquared]

I think the real problem is what it looks at. The shape of your face is what it looks at. What if you put a little clay or really thick makeup around your jaw and cheek bones to change your visible facial structure... and of course facial hair can be shaped to look like pretty much anything is under it without even adding anything artificial to your face. And of course, you'll need multiple frames of reference with a wide angle between them to get any useful information anyway... you can't really judge depth from a single frame and if you try a little eyeshadow will throw it off. I can only see facial recognition as proving that you aren't someone smaller then you are, not that you are a specific person. And of course you could always get one of those masks from mission impossible! Yea, that's what I thought!

Re:I've heard this for years

[Illserve]

Many other problems in CV are like this - edge detection, segmentation, etc. But people write hacks that work in restricted conditions and say they've solved.

Having worked in brain science for years I can say that the brain itself is a collection of hacks.

It's just a very huge collection that covers all of the bases that we find ourselves in from day to day. Put a brain in a situation it's not designed to handle and it breaks down just as badly as many artificial CV algorithms do.

Re:I've heard this for years

[lawpoop]

Brain hacks seem to be fundamentally different than computer hacks. Or, the brain seems to have a collection of hacks that we have almost no understanding of, in addition to the hacks that we do understand.

Ever since the advent of solid state electronics, it was said to be only a matter of time before robots would be sweeping, washing dishes, performing surgery, etc.

Things that we think are really simple, that even retarded people can do, like recognize a face or a voice, understand speech, move bipedally with grace (hell, with any number of legs -- 2, 4 or 6), pour a glass of water, etc. are *hard* for robots and AI. We don't even have a model for how these things work. Even really dumb animals like turkeys can run through their environments and successfully hunt and catch flying insects.

We do have robots that are getting good with articulation, like Asimo, but we still aren't sure whether they are using the same 'tricks' that organisms use. That is to say, they are a solution to the problem of bipedal motion, but we don't know if they are the same solution that the human mind is. I'm not sure that we have even a model of what solutions organisms use.

Meanwhile, things that we think are difficult, like playing chess, factoring polynomials, or other kinds of difficult math, are easy for a computer. Now we know that the brain can do complex math like trigonometry, in order to accomplish tasks like catching a ball. but that doesn't help the average person play chess or do complex math on paper. However, the average person excels at these hard AI problems, like having a conversation or pouring a glass of water.

recognized

[AcidLacedPenguiN]

This is all well and good, but the minute I get falsely identfied as a criminal just for being in the bar district late at night in the wrong place/wrong time I won't be too happy. . .

But I thought

[xirtap]

I thought they used chips in the eyes of people in minority report, not face recognition.

Re:But I thought

[john83]

I thought they used chips in the eyes of people in minority report, not face recognition.

Retina recognition, I think.

MyHeritage site

[LoverOfJoy]

I've tried out the software and it was fun for some laughs. I'm not sure how it works exactly but I can tell that the angle of the face makes a difference. When I put one picture of myself in where I'm looking ever so slightly to the right, I'm matched with celebrities photos looking in that direction. When I put in a similar photo facing the other direction, I get a different set of celebrities looking in the other direction. There's a few overlaps and those are the ones I think I look the most like (although it's a stretch to say I have anything that could pass as a celebrity look).

Inevitable.

[Lethyos]

Not to nitpick excessively, but you could easily substitute portions of this article with terms like (and relating to) “Internet”, “personal computer”, “telephone”, “car”, and others. Asking ourselves if a technology is “real or science fiction” when it already exists (albiet in a primitive form) is silly. Of course it exists; the question itself cites examples. Perhaps the meaningful questions might be along the lines of: “what are the challenges associated with making it accurate?” or “what impact will facial recognition have on society?”

Here to Stay

[DumbSwede]

I believe Minority Report used retina scans, but that nit aside facial recognition works to a degree and will only get better. Security cams will eventually upgrade to HDTV resolutions, perhaps augmented with very high resolution stills when a potential match is made. This will all take more processing power, but all mighty god Moore will eventually gives us this day our daily CPU load.

About false positives. So what? Eyewitnesses make mistakes also. Eventually, perhaps very soon, machines will surpass humans in this arena just as they have in others. Can anyone here on Slashdot defeat Deep Blue at Chess?

As to the legality or ethics, what can be done will be done, at least in public areas. If it would be legal for a human to do (they haven't outlawed humans scanning for suspects in public areas) then it will be legal for machines to do despite the unease many will feel knowing they are constantly being watched.

Re:Legal hoops

[Quadraginta]

Using a computer-captured image of your face in Court would presumably come under the same rules as using a photograph of your face. More or less, if you appear in public, your image can be used.

The more interesting question, I suggest, is whether a computer recognition of your face is going to be in any way equivalent to a human recognition of your face.

For example: if you stroll into a 7-Eleven, and the donuphage with a badge sitting there swilling coffee thinks you look like a famous bank robber whose mug has been circulated by the FBI, then he's entitled to take you into custody, and search you (for his own safety and those nearby, et cetera). If he finds half a gram of coke on you, you're in trouble. Now suppose it isn't the cop's eye/brain combination that "recognizes" you as a bank robber, but rather his shoulder-mounted camera/computer combination. Is he still entitled to act in the same way?

You can argue it both ways: (1) the camera/computer is almost certainly always going to be worse at this kind of thing than the eye/brain. Recognition is about the single most important thing our eyes and brains do, and they are highly optimized for it by natural selection. If it could be done better and faster, we would do it. So, we should trust the camera/computer less. But (2) the camera/computer is not subject to the vagaries of human psychology, mood, et cetera. The cop may take you in unreasonably because he doesn't like your skin color or length of hair, the camera/computer isn't subject to the same prejudices. So maybe it's better to trust the mindless device.

re: hacks and restricted conditions

[King_TJ]

But don't we almost always get a computer to solve a problem that's not strictly a mathematical one using "hacks that only work in restricted conditions"?

Our spell-checkers in our word processors don't actually know anything about the rules of a language, phonics, etc. They just do lookups from a dictionary. If a word's not listed, it has no idea if it's spelled properly or not -- even if the misspelling is one that's simply not a possible correct sequence of letters for the language. Most don't even realize if a word is misspelled in the context of the sentence, as long as it matches a correct spelling in the word list.

Until we figure out how the human brain recognizes faces as individuals, we can't expect anything *but* a clever hack for a computer to do the same. And truthfully, I suspect the human brain takes many things into account to do a "recognition" on a person. How often do you see somebody in the store that you're pretty sure you know from a previous job, school, etc. but you're not quite sure? I've had this happen a few times, and to make a better determination, I had to take other factors into account, like the sound of their voice if I heard them speak, the way they walked, or maybe an expression that came across their face. Humans "key in" on specific things that help them remember a person. And depending on which "features" they chose, they may or may not be effective. (Say you remember a gal really well because of her long, flowing hair? If she cuts it real short, there's a good chance you won't recognize her at all anymore if she walks by you.)

Re:Legal hoops

[B3ryllium]

or, maybe it's better to not carry a half-gram of coke on you.

Mathematical rigor is a part of vision

[AndOne]

I'm afraid I'm going to call shennanigans on some of this. I've been doing Vision work for about 5 years now with a hefty does of image and signal processing in the mix(Working as gradstudent in the field right now in fact). Edge detection is well defined. The canny and shah-istan(think that's the name) are about as close to a mathematical optimal edge detector as one can get. There is in fact a well developed body of theory regarding differentiation of Signals. The problem doesn't lie in the mathematical models involved. It lies in how many people want to use those models. Edge detection suffers from spurious edges or edge flakes which are a symptom of noise in the signal at differention(ie differentiation enhances noise, integration smooths it). Segmentation can also be well defined you just have to be clear on what it is you're segmenting. Are you working in a color space, texture, motion? That matters. However you can get some very good results in these fields. See GPCA techniques for some examples of doing it. Or even modified PCA + EM or PCA+ Kmeans(clustering theory). Again very well defined. Mathematically there are several models for face recognition. One can examine the ideas of eigen faces(not my personal favorite but it's there), kernel based SSD type approaches to find key points, partial face detection followed by recognition over a sequence of images used to reconstruct the face, and more. The problem isn't the math. It's that when you project a model you are essentially destroying an entire degree of freedom which is a huge deal. Further just as you can match a partial finger print or a partial ear print you can match partial facechunks. The problem with makeup or facial hair comes when one relies on global matching techniques or uses only 2d information to do the matching. Now I'll be a first to say that alot of computer vision is a solution in search of a problem or that people do use a number of cheap hacks and dirty tricks to get things working but saying it's not mathematical is a lie. I can turn around and see at least 3 books at a glance that detail the mathematics that are a part of vision and image processing. So please don't confuse peoples fuzzy use or lack of understanding of the math for there being no math. Note: Machines are also bad at a number of tasks humans are really good at but the same can be said that there are many tasks that humans are very bad at but the machines excel at. Absolute range detection is a good example. Humans are very bad at telling you the exact range to an object, even with some sort of scale of the scene reference. Computers on the other hand(while suffering from noise in the signal) are still able to achieve significant accuracy depending on the range. You can see tyzx for an example of a comany who makes highly accurate stereo rigs.(They were around as of 2 years ago at least and I assume they're still going strong) Cheers