Hardware and software solution furthers automotive forward camera innovation

Xilinx, Inc. and Motovis have announced that the two companies are collaborating on a solution that pairs the Xilinx Automotive (XA) Zynq SoC platform and Motovis’ CNN IP to the automotive market, particularly for forward camera systems’ vehicle perception and control. The solution builds upon Xilinx’s corporate initiative to give customers robust platforms to enhance and speed development.

“This collaboration is a significant milestone for the forward camera market as it will allow automotive OEMs to innovate faster,” said Ian Riches, vice president for the Global Automotive Practice at Strategy Analytics. “The forward camera market has tremendous growth opportunity, where we anticipate almost 20% year-on-year volume growth over 2020 to 2025. Together, Xilinx and Motovis are delivering a highly optimized hardware and software solution that will greatly serve the needs of automotive OEMs, especially as new standards emerge and requirements continue to grow.”

The forward camera solution scales across the 28nm and 16nm XA Zynq SoC families using Motovis’ CNN IP, a unique combination of optimised hardware and software partitioning capabilities with customisable CNN-specific engines that host its deep learning networks – producing a cost-effective offering at different performance levels and price points. The solution supports image resolutions of up to eight megapixels. OEMs and Tier-1 suppliers may now layer their own feature algorithms on its perception stack to differentiate and future-proof their designs.

“We are extremely pleased to unveil this new initiative with Xilinx and to bring to market our CNN forward camera solution. Customers designing systems enabled with AEB, and LKA functionality need efficient neural network processing within an SoC that gives them flexibility to implement future features easily,” said Dr Zhenghua Yu, CEO, Motovis. “With Motovis’ customisable deep learning networks and the Xilinx Zynq platform’s ability to host CNN-specific engines that provide unmatched efficiency and optimisation, we’re helping to future-proof the design to meet customer needs.”

“Expanding our XA offering with a comprehensive solution for the forward camera market puts a cost-optimized, high-performance solution in the hands of our customers. We’re thrilled to bring this to life and drive the industry forward,” said Willard Tu, senior director of Automotive, Xilinx. “Motovis’ expertise in embedded deep learning and how they’ve optimised neural networks to handle the immense challenges of forward camera perception puts us both in a unique position to gain market share, all while accelerating our OEM customers’ time to market.”