The Chinese government's plans for mass surveillance using facial recognition have received a boost from one of the country's tech powerhouses, after Alibaba led a $600m investment in SenseTime, which develops technology for tracking individuals. The company is working on facial and object recognition technology that accurately can spot people using cameras, recently demonstrated on CCTV in Beijing. Honda is using SenseTime for its driverless car research and development and it is also being used at shopping counters that allows customers to check-out using their faces. SenseTime already smashed the record for AI funding, beating British competitor DeepMind which was bought by Google for an...
Microsoft claims its facial recognition technology just got a little less awful. Earlier this year, a study by MIT researchers found that tools from IBM, Microsoft, and Chinese company Megvii could correctly identify light-skinned men with 99-percent accuracy. But it incorrectly identified darker-skinned women as often as one-third of the time. Now imagine a computer incorrectly flagging an image at an airport or in a police database, and you can see how dangerous those errors could be. Microsoft's software performed poorly in the study.
Facebook has boosted its face recognition capabilities with the acquisition of startup FacioMetrics. FacioMetrics uses facial image analysis to determine emotions, and is aimed at sectors including gaming, healthcare, augmented reality and robotics. Fernando De la Torre, founder and CEO of FacioMetrics said the company was formed to cater for the increasing interest in and demand for facial image analysis, with applications including augmented/virtual reality, animation and audience reaction measurement. The technology comes out of research at Carnegie Mellon University into developing computer vision and machine learning algorithms for facial image analysis. "Over time, we have successfully developed and integrated this cutting-edge technology into battery-friendly and efficient mobile applications, and also created new applications of this technology," said De la Torre.
The facial-recognition cameras installed near the bounce houses at the Warehouse, an after-school recreation center in Bloomington, Indiana, are aimed low enough to scan the face of every parent, teenager and toddler who walks in. The center's director, David Weil, learned earlier this year of the surveillance system from a church newsletter, and within six weeks he had bought his own, believing it promised a security breakthrough that was both affordable and cutting-edge. Since last month, the system has logged thousands of visitors' faces – alongside their names, phone numbers and other personal details – and checked them against a regularly updated blacklist of sex offenders and unwanted guests. The system's Israeli developer, Face-Six, also promotes it for use in prisons and drones. "Some parents still think it's kind of '1984,' " said Weil, whose 21-month-old granddaughter is among the scanned.
A team of engineering researchers from the University of Toronto has created an algorithm to dynamically disrupt facial recognition systems. Led by professor Parham Aarabi and graduate student Avishek Bose, the team used a deep learning technique called "adversarial training", which pits two artificial intelligence algorithms against each other. Aarabi and Bose designed a set of two neural networks, the first one identifies faces and the other works on disrupting the facial recognition task of the first. The two constantly battle and learn from each other, setting up an ongoing AI arms race. "The disruptive AI can'attack' what the neural net for the face detection is looking for," Bose said in an interview.