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CEA-Leti Unveils Autonomous Imager

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JOEL WILLIAMS, ASSOCIATE EDITOR
[email protected]

CEA-Leti has unveiled an autonomous imager technology that is able to activate smartphones and small appliances through facial recognition or other specific patterns, using 10,000× less power than similar technologies.

“The novel feature of the device is to allow a fully autonomous functioning of the image sensor, when in its surveillance mode,” CEA-Leti research director Antoine Dupret told Photonics Media. “Indeed, both the acquisition and the analysis of the scene are managed within the imager.”

The device is called μWAI (micro-WAY), and it’s about the size of a €1 coin, or a U.S. silver dollar. Its readout and processing architecture are co-designed with an algorithmic pipeline, in which the recognition results form a sequence of elementary algorithms to deliver ultralow power wakeup.

“In the surveillance ultralow power mode, the imager detects events within the scene,” Dupret said. “Upon the detection of a relevant event, the circuit first provides features for finer classification, then reverts into a standard image sensor functioning.”

Because the analysis occurs within the imager, rather than with the device’s primary computer system, power consumption is lower and the load on the computational system is reduced.

CEA-Leti's autonomous imager device µWAI. Courtesy of CEA-Leti.
CEA-Leti's autonomous imager device µWAI. Courtesy of CEA-Leti.
The device features automatic exposure adjustments according to the ambient lighting conditions, and an 88-dB dynamic range, as well as motion detection and feature-extraction for event-based functioning, and AI-based object recognition.

It can be easily implemented into smart devices already using cameras, as the smart sensing part of the circuit can be implemented in most image sensors.

The technology behind μWAI will be introduced during CEA-Leti’s Leti Innovation Days, June 22-23.
Edmund Optics - Manufacturing Services 8/24 MR

Published: May 2021
Glossary
machine vision
Machine vision, also known as computer vision or computer sight, refers to the technology that enables machines, typically computers, to interpret and understand visual information from the world, much like the human visual system. It involves the development and application of algorithms and systems that allow machines to acquire, process, analyze, and make decisions based on visual data. Key aspects of machine vision include: Image acquisition: Machine vision systems use various...
neural network
A computing paradigm that attempts to process information in a manner similar to that of the brain; it differs from artificial intelligence in that it relies not on pre-programming but on the acquisition and evolution of interconnections between nodes. These computational models have shown extensive usage in applications that involve pattern recognition as well as machine learning as the interconnections between nodes continue to compute updated values from previous inputs.
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