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Computer Beats Humans in Face Recognition for the First Time

Labeled Faces in the Wild Credit: LFWFacial recognition technology may be thwarted by photos' variations in pose, illumination, expression and occlusion. But for the first time, a computer algorithm, developed by researchers from Chinese University of Hong Kong, has beat the facial recognition accuracy of humans.

The researchers Chaochao Lu and Xiaoou Tang used the Labeled Faces in the Wild database – a collection of 13,000 faces of 6,000 public figures from the Internet, each labeled with the person's name – as a benchmark. The database provides a range of face images with variations in pose, lighting, expression, race, ethnicity, age, gender, clothing, hairstyles, and other parameters.

The algorithm, named GaussianFace, scored an accuracy rating of 98.52 percent, beating the human average of 97.53 percent. Prior to GaussianFace, the highest score achieved by technology was 97.25 percent. 

According to the Physics arXiv Blog, it works by normalizing each face into a 150x120 pixel image using five image landmarks: the position of both eyes, the nose and the two corners of the mouth. It then divides each image into overlapping patches of 25x25 pixels and describes each patch using a vector, which captures its basic features. Then it compare the images looking for similarities.

GaussianFace was trained by using four databases that contain very different images. One of these is the Multi-PIE database, which consists of face images of 337 subjects from 15 different viewpoints under 19 different conditions of illumination taken in four photo sessions. Another is a database called Life Photos, which contains about 10 images of 400 different people.


Retailers Turn to Facial Recognition to Cut Down on Shoplifting

Smile, shoppers. You're on candid camera equipped with facial recognition software.

Retail stores that are vulnerable to shoplifting criminal activity are about to get a new ally. FaceFirst, a facial recognition software system, recently partnered with a nationally renowned Fortune 500 company to deploy hundreds of cameras in store entrances across the nation in order to curb shoplifting incidences and other criminal activity in the retail market.

FaceFirst's national deployment is the retail industry's largest retail deployment of facial recognition, and the software company anticipates securing additional retailers in the future. The company claims its advanced facial recognition technology will boost customer loyalty by providing shoppers with a peace of mind knowing their shopping experience can be enjoyed without the threat of criminal activity.

The FaceFirst facial recognition system spots known perpetrators entering store locations so retailers can stop criminal activity before they cost the retailer money. The software allows retailers to receive descriptive alerts when pre-identified shoplifters walk through any door at any store across multiple locations and receive alerts when litigious individuals enter store locations.

FaceFirst is just the latest in a string of retail-oriented facial recognition applications. NEC just announced its NeoFace software, which recognizes returning customers and tracks their preferences to provide better customer service. Both FaceFirst and NeoFace are designed to be easily installed and fairly affordable, so retailers of all sizes can take advantage of the technology. As prices on this type of software continue to fall, shoppers should expect facial recognition to become increasingly popular in the retail world.


The Seamless Future of Augmented Reality 

With VENTURI's project Très Cloîtres Numérique, residents and visitors in Grenoble, a city in southeastern France, can soon use a tablet or smartphone to see the city in its past. The city scene is overlaid with historical photographs and 3-D reconstructions of ancient buildings. 

Companies like Volkswagen, Audi and IKEA are working with project partner Metaio to create exciting new tools. For example, Audi customers can take a virtual tour of their new vehicle; Volkswagen allows users to customize a car before ordering; and IKEA and Mitsubishi both allow customers to see how their products would look in their homes or offices, before buying.

But VENTURI researchers want people to experience augmented reality without tablets or smartphones. Their goal is to create a seamless augmented reality environment that leverages smart glasses, watches and earpieces. 

"In VENTURI, we have been exploring cutting edge 'reality sensing' through computer-vision and sensor fusion, and have tied this together with intuitive 'world augmentation' through 3D audio, Smartwatch interaction and HMDs like GoogleGlass," says VENTURI Project Coordinator Paul Chippendale. 

VENTURI is working with Metaio and Sony to create the first generation of ubiquitous AR tools. 

"Thanks to Sony's participation in VENTURI, we have had privileged access to their future vision of wearable devices, ranging from smart life logging bands (wrist-worn devices that log a user's activity) to advanced head mounted displaysm," Chippendale said. "We have been using this insight together with Metaio's strong market knowledge, to create personalised AR content according to a user's social profile, the current environmental and what it is that they're currently doing."


The FBI's Facial Recognition System Will Collect Data on Everyone -- Even Non-Criminals

Image credit: Electronic Frontier Foundation

Privacy fans, get ready to feel your blood pressure rise.

The FBI is planning to roll out an extensive new facial recognition system that includes a database of photos to identify Americans, regardless of criminal historyaccording to the Electronic Frontier Foundation.

The system, called Next Generation Identification, or NGI, could soon include facial rec information on as many as 100 million Americans. The FBI already maintains a database of about 100 million people’s fingerprints, as well as many retina scans and palm prints, and personal information like name, address, age and race.

According to Business Insider, the database will grow quickly. By 2015, the system will be able to query up to 52 million photos: 46 million criminal images, such as mugshots; 4.3 million "civil images" from other sources; and 215,000 photos from the Repository for Individuals of Special Concern.

NGI is already being used in several states, and many more will soon join in. According to privacy advocates like the EFF, the FBI is clearly overreaching the bounds of privacy.

According to the EFF:

[T]he FBI only ensures that “the candidate will be returned in the top 50 candidates” 85 percent of the time “when the true candidate exists in the gallery.”

It is unclear what happens when the “true candidate” does not exist in the gallery—does NGI still return possible matches? Could those people then be subject to criminal investigation for no other reason than that a computer thought their face was mathematically similar to a suspect’s? This doesn’t seem to matter much to the FBI—the Bureau notes that because “this is an investigative search and caveats will be prevalent on the return detailing that the [non-FBI] agency is responsible for determining the identity of the subject, there should be NO legal issues.”

We're interested to learn how the facial rec portion of NGI will work in reality. In the meantime, how do you feel about the FBI collecting and querying your facial recognition data? In today's age of dwindling privacy, does news like this still get under your skin?


Software Shows What Child Will Look Like in One Minute

In less than a minute, software can predict what a child will look like when he/she grows up. 

Developed by the University of Washington and funded by Google and Intel, the software automatically generates images of a young child’s face (photos that begin at age 5 work best) as it ages to age 80. This is the first fully automated approach for aging babies to adults that works with variable lighting, expressions and poses.

The software corrects for tilted faces, turned heads and inconsistent lighting, then averages thousands of random Internet faces of the same age and gender, and they are applied to the child's face to project his/her againg face. 

The renderings are so good that they are hard to discern from real photos. 

The researchers hope the software can factor in ethnicity, hair whitening and wrinkles in the future. 

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