I was sent a link to an article the other day and I am posting it on Crazy for Copiers as it is the wildest technological advance I have seen in quite some time - rather ingenious! I wish that copiers could have the such a feature embedded within eCopy that would detect spelling errors while scanning documents.
The original post was by Stephen Shankland CNet Networks on November 14, 2007.
MONTEREY, Calif.--Get ready for a new era in which your camera knows not just when you took a picture but who's in it, too.
Many cameras today can detect the faces of those being photographed,
which is handy for guiding the camera to set its exposure, focus, and
color balance properly. But the more difficult challenge of face recognition is more useful after the photo has been taken.

University
of California-San Diego researchers have turned expression-recognition
technology into an art exhibit showing the increasingly strained
efforts by models to maintain a chipper smile for more than an hour. A
buzzer goes off when a waning smile sends a monitor into the red zone.
(Credit: Stephen Shankland/CNET Networks)
That's because of a concept called autotagging, one of a number of
technologies that make digital photography qualitatively different from
the film photography of the past.
Tags of descriptive data can be attached to digital photos, and they
help people find and organize pictures. The only problem is that
tagging your photos, today a laborious manual task, is like eating your
vegetables. It's good for you but a lot of people don't like it.
With autotagging, the camera attaches tags as the pictures are
taken. Today, cameras embed timestamps in photos, which makes it
possible to sift through pictures by date. But be honest here--how
reliably can you remember exactly when you took that picture of your
darling daughter a year or two ago that you'd like to e-mail to her
grandparents? Being able to screen for photos only of a particular
person could dramatically speed up the search process.
Face recognition requires computational horsepower that is hard to
fit into the confines of a digital camera, but one company likely to
help make it a reality is Fotonation, which already supplies face-detection software for dozens of camera models from Samsung, Pentax, and others.
The computational challenge is reduced by the fact that most folks tend
to photograph the same set of 25 or 30 people, Eric Zarakov,
Fotonation's vice president of marketing, said in an interview here at
the 6sight digital imaging conference. A camera could be "trained" to recognize just those particular people.
He wouldn't comment on whether Fotonation plans to sell such software
to camera makers, but it sure looks likely. "We're looking at a lot of
stuff. That would be a natural extension" of today's product lines,
Zarakov said.
One camera maker willing to mention its interest in autotagging is
Panasonic. "A lot of thought is going into how to tag photos so you can
retrieve them at a moment's notice," said Alex Fried, national
marketing manager for imaging at Panasonic's Consumer Electronics Co.
But he wouldn't go into specifics: "There are things we have in the
works that will help benefit consumers going forward."
And faces aren't the only aspect of autotagging that's likely to
show up in cameras. Location, too, is another useful attribute that can
be attached to photos through a process called geotagging.
Geotagging can be used both to look for photos whose location you know
and to figure out what exactly is in a photo you already have at hand.
Today, geotagging is generally a laborious manual task that requires
geographic data to be merged with photos after the fact using a
computer. But more power-efficient approaches will lead to in-camera
GPS systems that will enable automatic geotagging, predicted Kanwar
Chadha, founder of GPS chip designer SiRF Technology.
"A location stamp is much more important than a time stamp in most
cases. A year down the road, you have no idea where those pictures were
taken and no way to search for location," Chadha said.
Face recognition is an area of active research and some commercialization. Start-up Riya
is working on technology to search through online photo albums to try
to identify individuals. Polar Rose is trying to improve recognition by
generating 3D models of faces. And 3VR wants to apply face recognition to what's become a highly lucrative market, security.

Software
from University of California-San Diego researchers, shown here at the
6sight digital imaging conference, can identify facial expressions.
This shot shows the nose-wrinkling detector in action, which Marian
Stewart Bartlett believes could be useful for market researchers.
(Credit: Stephen Shankland/CNET Networks)
But that's not the only research going on.
At the 6sight conference, Marian Stewart Bartlett showed results of her research into not just face detection, but expression detection. Her work at the Machine Perception Lab at the University of California-San Diego
lets a computer monitor 30 of the 46 codified components of facial
expressions. That includes movements such as raised eyebrows and
wrinkled noses.
In the demonstration, software tracked Stewart's face from a video
camera and recorded expression parameters. Analyzing the data, the
computer can draw conclusions about people. For example, when comparing
a video of a man's face as he experienced actual pain from immersing
his hand in cold water to another in which he faked the pain, people
had about an even chance guessing which showed the authentic pain. The
computer, though, had 72 percent accuracy, she said.
That level of sophistication is beyond a camera's abilities today,
requiring a full-fledged computer run by people with Ph.D. degrees. But
particularly given that Sony already has introduced a camera with smile
detection, it's not hard to imagine a day when your photos could also
some day be tagged "delighted" or "disgusted," too.
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