From seeing just the image of a face, computers will find its match in a database of millions of driver's license portraits and photos on social media sites. From there, the computer will link to the person's name and details such as their Social Security number, preferences, hobbies, family and friends.
Adding that capability to drones that can fly into spaces where planes cannot — machines that can track a person moving about and can stay aloft for days — means that people will give up privacy as well as the concept of anonymity.
In a real-time experiment, the scientists digitally mapped the face of "Suspect 2," turned it toward the camera and enhanced it so it could be matched against a database. The researchers did not know how well they had done until authorities identified the suspect as Dzhokhar Tsarnaev, the younger, surviving brother and a student at University of Massachusetts Dartmouth.
"I was like, 'Holy shish kabobs!' " Marios Savvides, director of the CMU Cylab, told the Tribune-Review. "It's not exactly him, but it's also not a random face. It does fit him."
Students working with Savvides are figuring out how to break up appearance into landmarks as unique as a fingerprint and to build a 3-D image from a single picture so it can be matched from different angles.
"The things we can do are endless," said Savvides. "We're basically decoding the face."
For now, the database holds only the images of lab workers and visitors who agree to participate. Savvides said he can envision a day when images collected by tiny cameras embedded in police cruisers and attached to officers' uniforms are matched against a database of wanted criminals. As soon as a driver looks into a rear-view mirror to see an officer pulling up, the person's face could be matched.
That technology does not exist, but the students have built a camera that collects facial identifiers from as far as 60 feet away.
Taken steps further using tiny drones that can fly over public areas and link to databases from social media sites, the technology might sweep down any American street and identify almost anyone instantly. Facebook users upload 2.5 billion images a month, but the company limits public access.
A separate research team at CMU has conducted experiments that matched photos of students on campus with their Facebook profiles — and then predicted their interests and Social Security numbers.
Not to worry, said Nita Farahany, a Duke University law professor who specializes in digital privacy. The U.S. Constitution will keep the government from peering into homes, and state laws block Peeping Toms.