Tag Archives | Facial Recognition

Computers Can Now Read Human Emotions Better Than You Can

emotionsThe logical end point is that we will abandon trying to interpret the moods and expressions on others’ faces, and instead rely on devices to instantaneously perform the task for us. Motherboard on a computer that Ohio State University researchers trained to recognize complex and subtle emotions far more skillfully than humans are able to:

For a while now, facial analysis software has been able to distinguish between the six “basic categories” of emotion—happiness, surprise, anger, sadness, fear, and disgust. If you asked me to do the same, I could probably do it. But when you drill down into complex, compound facial expressions such as “happily surprised,” “fearfully angry,” “appalled,” “hatred,” and “awed,” I’d probably blow a couple of them. This computer doesn’t. In fact, it can decipher between 21 different “complex emotions.”

It’s another step towards machines that can decipher what we feel… in [this] context, it’s easy to imagine a future filled with robotic companions and therapists.

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Cameras And Devices Will Soon Decode, Store, And Track Your Emotions

Emotient is one of many companies that plan to capture, analyze, and sell emotional information:

Emotient is the leading authority on facial expression recognition and analysis technologies that are enabling a future of emotion aware computing.

The company began at the Machine Perception Lab at University of California, San Diego, and has since attracted industry leaders across the realms of business, technology and science.

Emotient’s flagship products are the FACET™ SDK, a high-accuracy, cost effective and adaptive software development kit, and FACET™ Vision, a fully featured desktop application for automated facial expression analysis and video annotation. With a camera-enabled device, our system can quickly process facial detection and automated expression analysis in real-time.

Our leading-edge software detects and tracks primary expressions of emotion and blended composites of multiple emotions. Fortune 500 companies, market research firms, and a growing number of vertical markets are ideally suited to leverage facial expression data.

 

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Hi Def Cameras Can Now Capture The Reflection Of Your Face In Someone Else’s Eye

“Zoom in. Now enhance.” – Deckard, Bladerunner.

Via BoingBoing:

In Identifiable Images of Bystanders Extracted from Corneal Reflections, British psychology researchers Rob Jenkins and Christie Kerr show that recognizable images of the faces of unpictured bystanders can be captured from modern, high-resolution photography by zooming in on subjects’ eyes to see the reflections in their corneas. The researchers asked experimental subjects to identify faces captured from these zoomed-in images and found that they were able to do so with a high degree of reliability.

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New Company Training Software Uses Eye Recognition To Force You To Pay Attention

eyesAs much of our time as we spend watching screens, screens will soon be watching us. Businessweek writes:

Online training technology company Mindflash on Tuesday announced a new feature called FocusAssist for iPad that uses the tablet’s camera to track a user’s eye movements. When it senses that you’ve been looking away for more than a few seconds (because you were sending e-mails, or just fell asleep), it pauses the course, forcing you to pay attention—or at least look like you are—in order to complete it.

Sound kind of creepy, even Big Brother-y? Mindflash doesn’t think so. Donna Wells, the company’s CEO, writes in an e-mail: “Our focus is making sure trainees get all the information they need to do their jobs well.”

The feature was developed by a group of Stanford University Ph.D.s who also founded Sension, a “computer vision technology” company in Palo Alto that wants to use emotion- and facial-recognition technology to treat autism and Alzheimer’s disease.

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NYPD’s New Facial Recognition Unit Using Instagram And Facebook Photos To Identify Suspects

Social networking sites are a great way to meet and connect with new people, such as cops. DNAinfo New York writes:

Police are searching for suspects’ photos on Instagram and Facebook, then running them through the NYPD’s new Facial Recognition Unit to put a face to a name, DNAinfo New York has learned.

Detectives are now breaking cases across the city thanks to the futuristic technology that marries mug shots of known criminals with pictures gleaned from social media, surveillance cameras and anywhere else cops can find images.

[An] official explained how the new technology worked after a recent street robbery where a woman reported her jewelry stolen by her gal pal’s boyfriend. She did not know his name, only that he was likely in photos on his girlfriend’s Facebook page. “We did not have his name, but we found a photo and the Facial Recognition Unit got a hit.”

The new investigative entity was formally launched late last year, with eight cops working in teams of four manning the operations.

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PSYOPS 101: The Technology of Psych Warfare

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“As we have examined in this special series of Eyeopener reports on psychological warfare in recent weeks, Psychological Operations, or PSYOPS, are every bit as vital to military strategists today as they ever were. In fact, in this age of 24/7 online access and the possibilities for new battlegrounds in the “information battlespace” that it affords, Psyops may be even more important than they have ever been in “winning the hearts and minds” (or at least confusing and stupefying the hearts and minds) of enemies the world over.

In some ways, this is precisely the point. Psyops by their very nature tend to rely on mechanical and technological trickery to deceive enemies or sneak propaganda past their defenses. Some of the greatest military victories in history did not involve fighting or bloodshed at all, but merely intimidation through demonstration of technological superiority.”

Read more at CorbettReport.com

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How To Conceal Your Face From Machines

CV Dazzle is a project to develop a toolkit of styling and beauty-based methods to fight back against camera and computer facial recognition, allowing you to hide in plain sight:

The primary objective [is] thwarting face detection under the guise of high-fashion aesthetics. While there are several obvious approaches to hiding from face detection, some of these can be dismissed.

Sunglasses, for example, are a known occlusion which some algorithms account for. Wearing masks in public can be illegal. Hoods are popular and effective but make the wearer’s intent to hide too obvious. As an alternative, this project explores ways using ambiguously deceptive fashion.

CV Dazzle™ is camouflage from computer vision (CV). It is a form of expressive interference that combines makeup and hair styling (or other modifications) with face-detection thwarting designs. The name is derived from a type of camouflage used during WWI, called Dazzle, which was used to break apart the gestalt-image of warships, making it hard to discern their directionality, size, and orientation.

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FBI Begins $1 Billion Face Recognition Project

Expect plastic surgery to be a booming field starting in 2014. Via New Scientist:

As part of an update to the national fingerprint database, the FBI has begun rolling out facial recognition to identify criminals.

It will form part of the bureau’s long-awaited, $1 billion Next Generation Identification (NGI) programme, which will also add biometrics such as iris scans, DNA analysis and voice identification to the toolkit. A handful of states began uploading their photos as part of a pilot programme this February and it is expected to be rolled out nationwide by 2014. In addition to scanning mugshots for a match, FBI officials have indicated that they are keen to track a suspect by picking out their face in a crowd.

But privacy advocates are worried by the broad scope of the FBI’s plans. They are concerned that people with no criminal record who are caught on camera alongside a person of interest could end up in a federal database, or be subject to unwarranted surveillance.

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On How Computers See Race

Does technology covertly holds the biases of its creators? Alexis Stevens in Cluster Magazine writes about an unintended dimension of of facial-recognition-based surveillance software:

“HP Computers are Racist” is a 2009 YouTube video in which two electronics store employees demonstrate how face recognition and video tracking technology on Hewlett-Packard computers works more accurately for people of whiter skin tones. “I think,” one of the employees remarks with biting accuracy, “my blackness is interfering with the computer’s ability to—to follow me.”

The company issued an apology after the clip went viral, suggesting that face-detection algorithms have more difficulty identifying the contrast that helps discern facial structure in low lighting. An ironic outcome of this corporate oversight is that while black people are more likely to be eyed as suspicious and tracked in real life (e.g. stop-and-frisk), the engineering of webcams for a presumptively white target audience renders people of color more invisible to technology.

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