The ability of the latest developments in deep learning and neural networks to detect suspicious behaviour looks set to revolutionise law enforcement.
In the quest for a safer society, it looks increasingly like artificial intelligence will play a leading role. It seems that barely a week goes by without another report on the latest security application of facial recognition, with the technology being employed to check identities at the airport, along with a number of other emerging uses.
Berlin, for example, is currently trialling facial recognition cameras to spot known terrorists. Meanwhile, the Chinese city of Xinjiang has taken things a step further by arming its police officers with Google Glass-like headsets equipped with facial recognition scanners to help them to identify criminals.
The technology looks set to drag law enforcement into the 21st century, but facial recognition is just the start. Pioneers in AI-driven computer vision are developing more sophisticated technology that can read people’s emotions and more.
“Our latest emotion recognition technology understands every multi-layered element within images and videos in the same way humans do,” says David Fulton, CEO of WeSee. “This allows it to recognise and analyse images and faces in video content with up to 98% accuracy – and up to 1,000 times faster than the human brain.
“Harnessing the power of deep learning and neural networks, it can detect suspicious behaviour in real time through monitoring and analysing eye movement, gaze and micro-expressions, along with identifying seven key human emotions.”
The potential of emotion recognition is already exciting security companies and law enforcement organisations across the globe, due to its ability to determine an individual’s state of mind or intent through their facial cues, posture, gestures and movement. The fact that this can be done from different angles, and even if the subject is moving or partially obscured, say by a balaclava, as well as under various light conditions is particularly impressive. Dangerous objects can also be detected.
“Video cameras on a tube station platform, for example, could detect suspicious behaviour and alert police to a potential terrorist threat,” explains Fulton. “The same could be done with crowds at events like football matches. Nervousness and anxiety shown by someone using a cash point could be an indication that they are under threat or using a stolen bank card, triggering the machine to stop the requested transaction or alert the police.”
WeSee is currently experimenting alongside the Ministry of Defence’s JHub; an innovation hub based in WeWorks Aldgate that identifies and repurposes cutting edge technology to solve military problems. Their project seeks to understand how WeSee’s technology can use micro expression analysis to augment traditional situation analysis.
“We want to understand the potential of this technology and have been really impressed by the results so far,” says a JHub spokesperson. “We can imagine numerous applications for it in the defence and security sector.”
Fulton says WeSee is continually improving the technology, increasing both its speed an accuracy. The latest development is that it is the first emotion recognition technology that can be used on mobile devices, from laptops and tablets to smartphones, meaning it can now be deployed anytime and anywhere.
“More effective law enforcement and security in terms of better detection and prevention rather than increasing personnel and firepower will make for a safer society both on the streets and in the workplace,” he says. “Put simply, emotion recognition technology will make it easier to look after the good guys and help to catch the bad. Furthermore, spreading the word about what can be achieved across society should act as a great crime deterrent.
“Law enforcement is an essential focus for government, but also a very expensive one. Investing in the continual development of emotion recognition technology will not only deliver a safer society, but also more effective and efficient policing, potentially saving valuable funds – or at least using it more wisely.”
David Fulton is CEO at computer vision pioneers WeSee