Facebook has announced it now plans to unleash facial recognition technology with a new program that promises to identify the subject of an untagged image with nearly unparalleled accuracy.
Researchers at the social media giant claim that humans who look at two faces can identify if they are the same person with a 97.53 percent accuracy. They promise that the company’s new “DeepFace” program will be able to do the same with 97.25 percent accuracy.
Facebook users may have already noticed that the site is able to suggest friends to tag when a new picture is uploaded. It does so by analyzing the distance between an individual’s eyes and nose in both profile pictures and already tagged images.
The new DeepFace program will be much more intensive, using software to correct the angle of a face in an image, then comparing that to a 3D model of an average face. It then simulates what has been called a neural network to find a numerical description of the face. If there are enough similarities, Facebook will know if the faces are in fact the same.
DeepFace remains purely a research project for now. Facebook released a research paper on the project last week, and the researchers will present the work at the IEEE Conference on Computer Vision and Pattern Recognition in June. “We are publishing our results to get feedback from the research community,” says Taigman, who developed DeepFace along with Facebook colleagues Ming Yang and Marc’Aurelio Ranzato and Tel Aviv University professor Lior Wolf.
“This deep network involves more than 120 million parameters using several locally connected layers without weight sharing, rather than the standard convolutional layers,” the companyannounced.
“This we trained it on the largest facial dataset to-date, an identity labeled dataset of four million facial images belonging to more than 4,000 identities, where each identity has over a thousand samples. The learned representations coupling the accurate model-based alignment with the large facial database generalize remarkably well to faces in unconstrained environments, even with a simple classifier.”
DeepFace is still in the research stage and has not been exposed to the 1.23 billion Facebook users.
The team, which plans to announce the program in June at a computer vision conference, said it released the research paper last week to solicit the opinions of other qualified experts and gauge public opinion as a whole. That could perhaps be motivated by the number of questions that were raised when Facebook announced 18 months ago that it had purchased the Israeli startup Face.com for a reported price of approximately US$60 million.
With this announcement, Facebook’s acquisition of Face.com clarifies concerns about an Orwellian future inspired by news of the 2012 deal.
“As Facebook’s database develops, it’s conceivable that within a few years you could see someone on the street, point your iPhone at her, and pull up a list of possible identity matches within seconds,” Slate technology blogger Will Oremus wrote at the time.
“For now, Facebook only auto-suggests the identities of people who are among your friends. Still, the company will possess the information and capacity to identify and track people on a broad scale…Only the company’s concern for your privacy will stand in the way.”
Facebook founder and CEO Mark Zuckerberg, who phoned US President Obama last week to complain about the National Security Agency surveillance policies, announced earlier this year that the company has been investigating how to best implement AI technology in the future.
“The goal really is just to try to understand how everything on Facebook is connected by understanding what the posts that people write mean and the content that’s in the photos and videos that people are sharing,” Zuckerberg said on a conference call with investors earlier this year, as quoted by Bianca Bosker of the Huffington Post. “The real value will be if we can understand the meaning of all the content that people are sharing, we can provide much more relevant experiences in everything we do.”
Facebook has made it clear that the software, which automatically tags people in photos, isn’t going anyway anytime soon. In fact, facial-recognition software is growing and is being used and further developed by Facebook, Google, Apple and the U.S. government.
Carnegie Mellon University researcher Alessandro Acquisti showed how facial-recognition technology can be used with Facebook profile photos to match names and other identification data to pictures.
Acquisti presented his findings, alongside fellow researchers Ralph Gross and Fred Stutzman, at theBlack Hat Technical Security Conference in Las Vegas, according to tech website Cnet, which reported on the group’s presentation.
The researchers set up a computer webcam on the Carnegie Mellon campus and asked people to volunteer to have their pictures taken, Cnet said.
Those photos were then cross referenced with a database the team built of about 25,000 Facebook profile photos (all Facebook user names and photos are publicly shared with the world afterall), the report said.
The researchers found that facial recognition software identified 31% of the students by name, Cnet said.
Acquisti then demonstrated an app for Apple’s iPhone that can “take a photograph of someone, pipe it through facial-recognition software, and then display on-screen that person’s name and vital statistics,” the report said.
“Facial visual searches may become as common as today’s text-based searches” and that has “ominous risks for privacy,” Acquisti said in the Cnet report.