----- Original Message ----- From: "BlindNews Mailing List" 
<[EMAIL PROTECTED]> To: <[EMAIL PROTECTED]> Sent: Monday, 
October 22, 2007 9:21 PM Subject: CAPTCHAs For Social Good? (features GroZi)


Internet News.com Monday, October 22, 2007

CAPTCHAs For Social Good? (features GroZi)

By Susan Kuchinskas

Researchers at the University of California at San Diego have a plan to meld 
the brains of Internet users into a vast human grid that would make use of 
the seconds wasted on solving CAPTCHAs (define) to enact social change.

Likely familiar to any frequent Web user, CAPTCHAs are those 
difficult-to-see images comprised of squiggly letters and lines designed to 
confound blog spam bots and the like. Blogs and online forums typically use 
codes hidden in CAPTCHAs to prove that a poster is a human, rather than an 
automated program; ideally, a human user can see and enter a CAPTCHA's 
hidden code, while an automated program cannot.

While finding a hidden CAPTCHA code may take only a couple of seconds, when 
multiplied by the millions of other Internet users also responding to 
CAPTCHAs, those seconds can add up to hundreds of wasted hours.

The Soylent Grid project wants to apply those wasted seconds to identifying 
images for assistive technology applications.

The project, named in reference to the 1973 Charlton Heston film Soylent 
Green and its famous phrase, "Soylent Green is people!", is already well on 
its way toward developing ways to make use of time that would normally be 
spent on CAPTCHAs.

Soylent Grid's first application to harness tiny bits of Internet users' 
attention is GroZi Shopping Assistant, a program that helps visually 
impaired people with the difficult task of locating objects in stores.

LINK: http://grozi.calit2.net/

A joint mission between the California Institute of Telecommunications and 
Information Technology (CalIT2) and UCSD's Computer Science and Engineering 
departments, GroZi would use the Soylent Grid project to funnel to Web users 
images taken by visually impaired people, who can then identify the objects 
in those images.

GroZi relies on a wearable system with a camera and tactile/haptic feedback, 
a blind-accessible interface and computer vision-based object recognition 
software.

GroZi's human need

But without Soylent Grid's human factor, GroZi faces difficult technical 
hurdles. Recognizing content in digital images has long been a nut difficult 
for computer science to crack. The human brain, on the other hand, is superb 
at recognizing content in images, knowing immediately which object in a 
family photo is Uncle Sean and which is the family dog.

For the GroZi prototype, it took developer Michele Merler, now at Columbia 
University, weeks to input the 120 products found in a single 45-minute 
video. To make the system truly useful, however, GroZi would need to be able 
to decipher the staggering array of items available in modern stores within 
seconds.

Enter Soylent Grid. Instead of building an image database item by item, the 
project could take advantage of time spent identifying CAPTCHAs. In such a 
scenario, the system could test a user attempting trying to post on a blog 
by asking them to decipher a GroZi photo instead of a traditional CAPTCHA.

The idea is to do this in real time, so that a visually impaired person at a 
grocery store could use GroZi to tell the corn niblets from the creamed 
corn.

"The currently used types of CAPTCHAs are a complete waste once they go 
stale," said Stephen Belongie, the UCSD professor who heads the project. 
"They're totally artificial, and when hackers crack them, their approach is 
invariably 'hacky' and neither reveals any insight into human object 
recognition nor does it do any good for society as a whole."

While efforts in other industries are being made to improve image 
recognition -- search engines, for example, are interested in 
image-recognition technology to improve their search results -- a 
human-powered system like the GroZi-Soylent Grid effort could vastly improve 
the lives of the blind and vision-impaired.

Researchers outlined the benefits (PDF file) of Soylent Grid earlier this 
week in a paper presented at the Interactive Computer Vision 2007 conference 
in Rio de Janeiro.

LINK: 
http://vision.ucsd.edu/~vrabaud/papers/SteinbachRabaudBelongieICV07SoylentGrid.pdf

Soylent Grid, GroZi, and CAPTCHAs

For a Soylent Grid/GroZi combination to make an impact, however, the service 
would need to partner with one or more online entities that make heavy use 
of CAPTCHAs, such as blogging platforms or social media sites.

For example, the Soylent Grid team estimates that Digg users could identify 
an image approximately every 17 seconds. That's far from fast enough for 
someone hurrying through their shopping. Belongie estimates that five 
seconds would be an acceptable turnaround time, so GroZi would need 25 times 
the CAPTCHA-producing power of Digg.

Image-recognition as part of a live video feed is an even more remote 
possibility.

"The idea of doing real-time object recognition on a live video stream is at 
the fantasy end of the Soylent Grid spectrum," Belongie said in an e-mail 
interview. "In reality, we expect it will be more likely to have an 
increased role for the computational processing component, so that the 
available human cycles are employed more opportunistically.

Ideally, every product identified would go into a standalone database, 
eventually enabling quicker lookups for GroZi that wouldn't require the 
input of Web users. This ultimately could allow the Soylent Grid project to 
be harnessed for other endeavors.

"If the initial GroZi box had some amount of computational power ... it 
could be pulled off the grid and run locally on the GroZi box in the user's 
hand, or run remotely on a private-GroZi-only computational system of much 
smaller scale," said Stephan Steinbach, another Soylent Grid project member.

Soylent Grid is an example of crowdsourcing, the notion of bringing together 
masses of users to accomplish what no individual or company could.

LINK: http://www.internetnews.com/infra/article.php/3614451

HumanGrid, launched in December 2005, is another example of applying 
crowdsourcing to labor-intensive tasks. The HumanGrid marketplace, in 
private beta, aims to introduce businesses and researchers to individuals 
willing to perform micro-tasks for micro-payments, such as data enhancement, 
text classification, transcription and picture classification.

LINK: http://www.humangrid.eu/

Amazon's Mechanical Turk service is another example; It's a similar 
automated marketplace where businesses can offer to pay humans to do tasks 
like tagging objects found in images or selecting the best photos of a 
product from a set of images.

The e-tailing giant developed the technology to help sort out the 20 million 
photos of storefronts to be used in its A9 Yellow Pages local search 
product.

LINK: http://www.internetnews.com/xSP/article.php/3465211

Belongie said that Soylent Grid has a better chance of succeeding because 
its strategy of distributing the work via third-party sites creates an 
ecosystem.

"For all three main parties involved -- the researchers, the Web sites, and 
the users -- there's something in it for them," he said. Researchers, 
whether academic or commercial, "have data they need labeled, for which one 
assumes they'd be willing to pay ... for example, someone wanting to spot 
pizza storefronts or real estate posters in Google Street views footage."

"Web site owners want a fresh source of CAPTCHAs, since the ones they use 
routinely go stale, meaning they get cracked by hackers in the Ukraine," he 
added. "And the users simply want to get to whatever content lies behind the 
CAPTCHA."


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