"Computers have been getting better and better at seeing movement on video. How is it that they read lips, follow a dancing girl or copy an actor making faces?"
– from Andrew Blake. Introduction to Active Contours and Visual Dynamics. Visual Dynamics Group, Department of Engineering Science, University of Oxford
Apple has published its latest machine learning journal entry with a new article detailing the challenges of implementing facial detection features while maintaining a high level of privacy. Apple started using deep learning for face detection in iOS 10. With the release of the Vision framework, developers can now use this technology and many other computer vision algorithms in their apps. We faced significant challenges in developing the framework so that we could preserve user privacy and run efficiently on-device. Apple's iCloud Photo Library is a cloud-based solution for photo and video storage.
Tech companies are eyeing the next frontier: the human face. Should you desire, you can now superimpose any variety of animal snouts onto a video of yourself in real time. If you choose to hemorrhage money on the new iPhone X, you can unlock your smartphone with a glance. At a KFC location in Hangzhou, China, you can even pay for a chicken sandwich by smiling at a camera. And at least one in four police departments in the US have access to facial recognition software to help them identify suspects.
When you upload photos to Facebook, have you noticed that the website already seems to know who's in them? It's remarkable, and you can give the credit to big data. Face recognition software, like fraud detection and ad matching algorithms, draws on deep libraries of content in order to deliver the correct results. And these data collections are hard at work across the web and in many of your favorite apps. It comes as no surprise that developers have been hard at work on face recognition software since it's an integral part of security programs.
There is no such thing as foolproof phone security. Case in point: Security researchers at Bkav have reportedly defeated the iPhone X's Face ID feature using a simply-constructed 3D mask. The average person probably doesn't need to worry about the purported hack, but billionaires, celebrities, and high-profile public figures like presidents may want to rethink their use of Apple's nascent facial recognition technology. Apple is trying to convince people Face ID is more secure than its Touch ID fingerprint sensor, which is still used in the iPhone 8 in addition to earlier models. But stories about weak spots (especially if you've got a twin or you're a kid) keep popping up.
It's one of the most wanted features in the iPhone X, but it seems that Face ID may not be as safe as Apple thinks. Cyber-security researchers claim they have fooled the face recognition technology with a mask that costs just £114 ($150) to make. The findings suggest that face recognition is not yet mature enough to guarantee security for computers and smartphones, according to the researchers. The main frame of the face was created with a 3D printer, and the nose was created by an artist from silicone. The eyes were represented with 2D images, while the'skin was also hand-made to trick Apple's AI', according to the researchers.
What happens when a tech artist and her gene-scientist husband try to wow the crowd at a "Nerd Nite" event in Kendall Square? They pitch an idea for an app to help fight disease by crowd-sourcing millions of 3-D digital maps of human faces. Facetopo was the brainchild of Boston documentarian and artist Alberta Chu and her husband Murray Robinson, whose brother was diagnosed with a rare disease that, like Down's syndrome, can be detected in the face. In a Q&A with Patch, Chu says some day participants could "maybe trade pictures, or eventually, find a twin." "Every user who wants to participate creates a private account and is able to download the app on either IOS or Android where we provide instructions so that you can create a 3-D face map.
On the first day of school, a child looks into a digital camera linked to the school's computer. Upon a quick scan, the machine reports that the child's facial contours indicate a likelihood toward aggression, and she is tagged for extra supervision. Not far away, another artificial intelligence screening system scans a man's face. It deduces from his brow shape that he is likely to be introverted, and he is rejected for a sales job. Plastic surgeons, meanwhile, find themselves overwhelmed with requests for a "perfect" face that doesn't show any "bad" traits.
The results are in from the biggest computer face-recognition contest to date. Everyone from government agencies to police forces are looking for software to track us in airports or spot us in CCTV images. But much of this technology is developed behind closed doors – how can we know if any of it really works? To answer this question, the Intelligence Advanced Research Projects Activity (IARPA) and the US National Institute of Standards and Technology (NIST) have been running the biggest face-recognition competition to date. The Face Recognition Prize Challenge tested two tasks: face verification and face search.
Now that all of its launches for 2017 are done, Apple is working on its 2018 devices, according to a Bloomberg report Wednesday. The company is expected to follow its yearly cycle launching the iPad first, followed by the iPad Pro and then the iPhones in the fall. Apple remains the sole industry player that is still developing tablet PCs and therefore, its affordable tablet is an important device for the segment. The company is not expected to endow the 2018 iPad with a long-awaited feature though -- an iPhone X style super retina OLED display, according to Bloomberg's Mark Gurman. FaceID: Apple is expected to endow the new iPad with the FaceID face recognition system.
Voters have a right to keep their political beliefs private. But according to some researchers, it won't be long before a computer program can accurately guess whether people are liberal or conservative in an instant. All that will be needed are photos of their faces. Michal Kosinski – the Stanford University professor who went viral last week for research suggesting that artificial intelligence (AI) can detect whether people are gay or straight based on photos – said sexual orientation was just one of many characteristics that algorithms would be able to predict through facial recognition. Using photos, AI will be able to identify people's political views, whether they have high IQs, whether they are predisposed to criminal behavior, whether they have specific personality traits and many other private, personal details that could carry huge social consequences, he said.