Funded by EPSRC, The three-year £1.3m project, which also involves King's College London and University College London, will explore potential applications of newly developed “neuromorphic” sensors: devices which mimic the way a mammal’s eye processes information.
Explaining the drawback of existing imaging systems the leader of the Kingston team, Professor Maria Martini, said: "Conventional camera technology captures video in a series of separate frames, or images, which can be a waste of resources if there is more motion in some areas than in others,” she said. "Where you have a really dynamic scene, like an explosion, you end up with fast-moving sections not being captured accurately due to frame-rate and processing power restrictions and too much data being used to represent areas that remain static.”
In contrast, the neuromorphic sensors – developed for the project by sensor specialist iniLabs - mimic the mammalian eye by sampling different parts of the scene at different rates, acquiring information only when there are changes in the light conditions.
This dramatically reduces the energy and processing needs for the cameras and during the research project the team will look at how high-quality footage could be sourced efficiently from the dynamic visual sensors and then shared between machines or uploaded to a server in the cloud.
"This energy saving opens up a world of new possibilities for surveillance and other uses,” said Martini, “from robots and drones to the next generation of retinal implants. They could be implemented in small devices where people can't go and it's not possible to recharge the battery.
As part of the project, the team will be looking at how these sensors could work together as part of the Internet of Things (IoT) – devices that can be connected over the internet and then operated remotely.
Project partners include global technology firms Samsung, Ericsson and Thales, as well as semiconductor company Mediatek and neuromorphic sensor specialist iniLabs.
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