"... the research area that studies the operation and design of systems that recognize patterns in data." It includes statistical methods like discriminant analysis, feature extraction, error estimation, cluster analysis.
– Pattern Recognition Laboratory at Delft University of Technology
As image recognition advances continue to accelerate, startups with a mind towards security applications are seeing some major interest to turn surveillance systems more intelligent. AnyVision is working on face, body and object recognition tech and the underlying system infrastructure to help companies deploy smart cameras for various purposes. "It's not just how accurate the system is, it's also how much it scales," Etshtein tells TechCrunch. "You can put more than 20 concurrent full HD camera streams on a single GPU." The Tel Aviv-based AI startup announced today that it has closed a $28 million Series A funding round led by Bosch.
Whether you're interested in learning how to apply facial recognition to video streams, building a complete deep learning pipeline for image classification, or simply want to tinker with your Raspberry Pi and add image recognition to a hobby project, you'll need to learn OpenCV somewhere along the way. The truth is that learning OpenCV used to be quite challenging. The documentation was hard to navigate. The tutorials were hard to follow and incomplete. And even some of the books were a bit tedious to work through. The good news is learning OpenCV isn't as hard as it used to be. And in fact, I'll go as far as to say studying OpenCV has become significantly easier. And to prove it to you (and help you learn OpenCV), I've put together this complete guide to learning the fundamentals of the OpenCV library using the Python programming language. Let's go ahead and get started learning the basics of OpenCV and image processing. By the end of today's blog post, you'll understand the fundamentals of OpenCV.
Microsoft president Brad Smith speaks at the 2017 annual Microsoft shareholders meeting in Bellevue, WA. (AP Photo/Elaine Thompson) This morning Microsoft President Brad Smith posted an essay on the company's blog that raises important questions about the human rights challenges related to facial recognition technology. Microsoft, and in particular, Smith, have led the tech industry in addressing human rights issues that inevitably grow from the spreading use of emerging technologies. As Smith points out, these new technological capacities are often a force for good, but are also subject to manipulation and can cause great harm. What is clear is that these new technologies are now part of our lives and will play an ever-greater role in the future. Smith rightly focuses on vexing challenges relating to the governance of facial recognition technologies, a rapidly evolving area which requires new models in which both governments and companies assume greater responsibilities.
The label of Black Red Ale beer, which incorporates a large "talking" skull, fully fits into the smart packaging trend by using advanced AR facial recognition and dynamic scenarios dependent on users' emotions. NRC is a set of communication protocols that enables two electronic devices, one of which is often a portable smartphone, to establish communication and AR is the interactive experience of a real-world environment, which has been "augmented" digitally. Click to EnlargeAs the customer scans the smart label with a mobile app, the skull presented on the label engages in an interactive dialogue with the consumer. The facial recognition feature detects if the customer is happy or sad and customizes the next part of the dialogue to accommodate a flowing conversation. Furthermore, variable AR scenarios are also launched depending on answers provided to questions asked by the skull.
Facial-recognition technology is improving by leaps and bounds. Some commercial software can now tell the gender of a person in a photograph. When the person in the photo is a white man, the software is right 99 percent of the time. But the darker the skin, the more errors arise -- up to nearly 35 percent for images of darker-skinned women, according to a new study that breaks fresh ground by measuring how the technology works on people of different races and gender. These disparate results, calculated by Joy Buolamwini, a researcher at the Massachusetts Institute of Technology Media Lab, show how some of the biases in the real world can seep into artificial intelligence, the computer systems that inform facial recognition.
A creepy surveillance start-up backed by the Chinese government is expanding its artificial intelligence-powered face-reading operations. Beijing firm Megvii has announced it is shifting its powerful Face facial recognition technology beyond China after securing a distributor in Thailand. Megvii's world-leading Face technology uses AI to identify people by their facial features, allowing police to spy on'anyone, anywhere' without them knowing. The software has already been used by Chinese police departments to arrest more than 3,000 fugitives by instantly scanning crowds of thousands in busy cities. The company says its software has many potential uses beyond law enforcement, including in financial services, retail, and identity verification.
Kairos snaps up EmotionReader, which can scan faces in a crowd and tell how audiences are reacting. EmotionReader, an Enterprise Ireland-backed facial recognition start-up, has been acquired by Miami-based Kairos in an undisclosed "multimillion-dollar" deal. Artificial intelligence (AI) then analyses viewer attention and emotional response, enabling media and brand owners to collect actionable insights and analytics for video. 'In our mission to fix biases in today's face recognition algorithms, we're thrilled to welcome to Kairos some of the best deep-learning talent in the world' – BRIAN BRACKEEN The company is the brainchild of Dr Padraig O'Leary and Dr Stephen Moore, and it was founded only last year. Moore, working from his Singapore base, is understood to have built an impressive R&D team in the south-east Asian country.