Ambarella introduces 4K SoC with computer vision architecture

Ambarella introduces 4K SoC with computer vision architecture
Ambarella, a developer of low-power, HD and Ultra HD video processing semiconductors, introduced the CV22 camera SoC, combining image processing, 4Kp60 video encoding and CVflow computer vision processing in a single, low power design.

The CV22’s CVflow architecture provides the DNN (Deep Neural Network) processing required for the next generation of intelligent home monitoring, automotive, drone and wearable cameras. Fabricated in advanced 10nm process technology, it achieves an industry-leading combination of low-power and high-performance in both human vision and computer vision applications.

“CV22 enables customers to deploy cameras with high-performance deep-learning capabilities,” said Fermi Wang, CEO of Ambarella. Compared with inefficient CPU and GPU solutions, CV22 provides powerful computer vision performance combined with high-quality image processing, efficient video encoding and the low-power operation required to be deployed in mass production. “It will enable a new level of intelligence in cameras, ranging from person recognition in home monitoring cameras to advanced ADAS capabilities in automobiles,” Wang said.

The CV22’s CVflow architecture provides computer vision processing at full 4K or 8-Megapixel resolution at 30 frames per second, to enable image recognition over long distances and with high accuracy. It includes efficient 4K encoding in both AVC and HEVC video formats, delivering high-resolution video streaming with very low bitrates to minimize cloud storage costs.

The CV22’s next-generation ISP (Image Signal Processor) provides outstanding imaging in low light conditions while HDR (High Dynamic Range) processing extracts maximum image detail in high contrast scenes, further enhancing the computer vision capabilities of the chip. It includes a suite of advanced security features to prevent hacking, including secure boot, TrustZone and I/O virtualization.

A complete set of tools is provided to help customers to easily port their own neural networks onto the CV22 SoC. This includes compiler, debugger and support for industry standard training tools including Caffe and TensorFlow, with extensive guidelines for CNN (Convolutional Neural Network) performance optimizations.

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