Quadric and AMS Osram collaborate on intelligent image sensors
The solution enables new capabilities of low power and small form factor smart sensing for various applications, for example, face detect and identification, human pose detect, motion and occupancy detect, and many others.
Quadric, an innovator in machine learning processor IP for on-device AI, and AMS Osram launched a strategic collaboration to develop integrated sensing modules combining AMS Osram’s leading edge Mira family of CMOS sensors for visible and infrared with Quadric’s novel Chimera GPNPU processors. The combined ultralow power modules will enable new methods of smart sensing for wearable devices, robotics, industrial and security markets. A demonstration of the product was on display at CES Las Vegas earlier this month.
Quadric’s Chimera general purpose neural processors (GPNPUs) offer the ability to handle both machine learning graph processing and classical data-parallel C++ algorithms in a unified architecture, bringing advanced on-device AI capabilities to edge-based applications. Quadric's architecture delivers efficient machine learning (ML) inference performance, but unlike other neural network accelerators which support a limited number of machine learning graph operators, the Quadric solution also has general-purpose control and signal processing capability – blending the best attributes of NPU accelerators with DSPs.
The Mira lineup of CMOS image sensors from AMS Osram are focused on low sensor and system power, and small form factors that maximize resolution efficiency in minimal footprint. The growing portfolio of the Mira family sensors offer a range of resolutions for different applications requiring high performance global shutter image sensors, multiple released products and more in development at higher and lower resolutions.
“The combination of AMS Osram’s sensors and Quadric’s processing into a single low-power module opens up vast new possibilities for deployment of smart vision sensing,” said Joost Seijnaeve, vice president and general manager of CMOS image sensors for AMS Osram. “OEMs no longer need 5-W edge silicon chips or 15-W board-level compute solutions to perform smart sensing functions like human pose, face identification, object detection, object recognition, and scene analysis,” continued Mr Seijnaeve. “Those leading-edge smart vision functions can be embedded in a single combined sensor and processing module in a host of innovative product form factors in automotive, consumer, industrial and applications.”
A Mira image sensor combined with a Quadric GPNPU integrates image capture and machine learning into a single low-power module – accomplishing in a few hundred milliwatts what today requires a 5W or 10W GPU card according to simulations run by Quadric. The Mira220 and future derivative resolutions offer multiple combinations for different applications combined with Quadric’s scalable Chimera processor lineup that spans a range of compute from 1 TOP to 16 TOPs.
“Quadric is excited to be joining forces with AMS Osram,” said Quadric CEO Veer Kheterpal. “Empowering device makers with the capability for a fully-programmable smart sensing device at incredibly low power levels will open a vast new tranche of deployments of machine learning in edge devices.”
