First autonomous imager for smartphones appliances and automobiles

01-06-2021 | CEA-Leti | New Technologies

CEA-Leti has announced what it claims to be the world’s first autonomous imager technology that activates smartphones and small appliances via face recognition or other particular patterns.

Called µWAI (micro-WAY) and sized as small as a 1€ coin, the autonomous imager provides a novel readout and processing architecture co-designed with an optimised algorithmic pipeline, in which the recognition results from a sequence of elementary algorithms, to give ultralow-power wake-up modes and compact silicon implementation to keep prices down.

It is the first smart image sensor jointly offering auto-exposure for all lighting conditions and 88dB dynamic range, plus motion detection and feature extraction for event-based functioning and AI-based object recognition that triggers extremely reliable identification. These key features also facilitate highly reliable decision-making for a few tens of pJ/pixel/frame, which outperforms current off-the-shelf systems. The pJ/pixel/frame measures the energy consumed by each pixel for every single image within a frame of images. A typical implementation needs about 10,000 times more energy than µWAI.

Applications and functions include automatic switching and face identification in mobile devices, contactless smart switching of household appliances and sport-and-entertainment devices in smart homes. It also offers face recognition, people counting, alarm triggering in smart buildings, driver identification, vehicle-interior situation awareness, parking-situation awareness and a smart-unlocking system in automobiles.

“The recognition engine is optimised to recognise faces when movement is detected. CEA-Leti’s team is working hand-in-hand with STMicroelectronics to develop specific smart-imager products as we consider extending the technology to other use cases,” said Antoine Dupret, CEA-Leti’s industrial partnership manager. “We target adapting the recognition engine as IP embedded in various cameras and optimising the performance of the imager to the requirements of our partner’s customers.”

By Natasha Shek