A GMDA official said that in line with the requirement of the police, the cameras will be used for general surveillance. Using artificial intelligence, the cameras will support in detection and tracing of people with a criminal record and missing persons, the official added. Six face recognition cameras had earlier been installed on the Sheetla Mata temple premises, four at the Gurgaon bus stand and one at Sadar Market exit. "The GMDA is closely working with the police and traffic departments in understanding their requirement for installing these cameras equipped with state-of-the art technology across the city. These cameras provide live feeds to the integrated command and control centre which is commissioned and working in GMDA, as well as to eight other monitoring police stations in Gurgaon. We aim to increase our scope of surveillance across the geographies falling under GMDA jurisdiction in Gurgaon and Manesar," said GMDA CEO Sudhir Rajpal in a statement.

SPRINGFIELD, MASSACHUSETTS – Police departments around the U.S. are asking citizens to trust them to use facial recognition software as another handy tool in their crime-fighting toolbox. But some lawmakers -- and even some technology giants -- are hitting the brakes. Are fears of an all-seeing, artificially intelligent security apparatus overblown? Not if you look at China, where advancements in computer vision applied to vast networks of street cameras have enabled authorities to track members of ethnic minority groups for signs of subversive behavior. American police officials and their video surveillance industry partners contend that won't happen here.

Short video has become the main form of online entertainment for a growing number of netizens. As a platform enabling anyone anywhere to express themselves and share their lives with huge online communities, Short video has generated a thriving culture. Artificial intelligence has penetrated into various areas of the short video ecosystem, but most visibly through technologies related to computer vision, face recognition, feature acquisition, image semantic segmentation and so on, which have helped creators build and present more diverse online personas. Short video is well positioned to grab a piece of China's growing online video industry market, which jumped from CN¥24.9 billion (US$3.5 billion) in 2014 to CN¥95.2 billion (US$13.5 billion) in 2017 and is expected to reach CN¥191.6 billion (US$27.1 billion) in 2020. TikTok is a Chinese video app for social media that launched globally in 2017.

Facial recognition systems are all the rage among government agencies around the world, as they seek to automate services and keep tabs on their citizens. If there's a picture of you somewhere, you could potentially be identified in photos and videos from public camera feeds. Now, Facebook has devised a way to thwart this technology. Its face de-identification tech, developed by three AI researchers who work with the company, modifies your face slightly in video content, so that facial recognition systems can't match what they see in the footage with images of you in their databases. You can see this in action in this video (screenshot above), in which certain details are tweaked, such as the shape of a person's mouth, or the size of their eyes.

Let's face it, any technology that lets us skip a step is a welcome move. But, since these features often collect and use massive amounts of very personal information, there will always be that nagging question on just how is it being used. That question was what dragged Facebook to the court in April this year after it was discovered the digital behemoth was using facial data without user consent. Apparently, Facebook had resorted to using "face templates" in its tag suggestions without letting anyone know. The debacle has worked as a sort of a warning shot to other companies that utilize biometric data to deliver services.

US lawmakers have asked the Government Accountability Office to examine how face recognition technology is being used by companies and law enforcement agencies. The questioners: A group of Democrats from both the House of Representatives and the Senate sent a letter to the GAO asking to examine which agencies are using the technology, and what safeguards the industry has in place. Some form of government regulation could eventually be imposed. Eye spies: There is growing concern that unfettered use of facial recognition could enable greater government surveillance and automate discrimination. Some companies also appear concerned.

Facebook is notifying more users of its facial recognition features as it faces increased scrutiny over how the technology may infringe upon their privacy. Many users who logged onto Facebook on Tuesday reported seeing a message from the firm on their News Feed outlining several new facial recognition features. Facebook now notifies users when someone uploads a picture of them that they haven't been tagged in, among other features. Facebook notified some users on their News Feeds of the firm's new facial recognition technology. The features tell users when a photo of them has been uploaded to Facebook that they haven't been tagged in yet and if a stranger uses a photo of them as their profile picture The features were first announced last December, but Facebook has been gradually rolling them out over the past several months.

What can your face say about you? Face recognition technology can pick up on things like your age, gender and maybe even your mood. Now, two researchers say it could even tell whether you're a criminal. They are claiming to have developed a system that, when shown a series of faces it has never encountered before, can pick out the ones belonging to convicted criminals. But other researchers have criticised the results, and say the work raises ethical questions over what face recognition technology can and should be used to detect.

Those new glasses make you look completely different – especially to face recognition software. A team of researchers from Carnegie Mellon University has fooled face recognition algorithms using the oldest trick in the book: a pair of fake glasses. By printing bespoke patterns onto the front of the frames, they enabled wearers not only to obscure their identity but to impersonate people who look completely different, at least in the eyes of the algorithms. A white male researcher wearing the glasses was able to pass for American actress Milla Jovovich while a South-Asian female colleague was digitally disguised as a Middle-Eastern male. The system wasn't perfect, however: a Middle-Eastern male trying to use the glasses to pass as white British actor Clive Owen only succeeded 16 per cent of the time.