CEVA, a leading licensor of signal processing IP for smarter, connected devices, has announced that Rockchip, China’s leading fabless semiconductor company, has licensed the CEVA-XM4 imaging and vision DSP to enhance the imaging and computer vision capabilities of its’ System-on-Chip (SoC) product lines targeting smartphones, ADAS, drones, robotics and other smart camera devices.
Rockchip will leverage the CEVA-XM4 for a range of advanced imaging and vision features at low power consumption among which include low-light enhancement, digital video stabilisation, object detection and tracking, and 3D depth sensing. In addition, the CEVA-XM4 will enable Rockchip to use the latest deep learning technologies, utilising CEVA’s comprehensive Deep Neural Network (CDNN2) software framework.
‘Rockchip is determined to deliver ever-more compelling solutions for mobile and consumer devices, using the best-of-breed technologies available,” said Feng Chen, chief marketing officer of Rockchip. “The CEVA-XM4 imaging and vision processor and comprehensive software offering allows us to truly embrace the potential of computational photography, computer vision and machine learning in our product designs, seamlessly handling even the most complex use cases and algorithms.”
“CEVA and Rockchip have a long and successful partnership incorporating multiple generations of our imaging and vision DSPs shipping in tens of millions of Rockchip-based devices to date,” said Gideon Wertheizer, CEO of CEVA. “This latest agreement will enable Rockchip to significantly strengthen its offering in the exciting realm of computer vision and provide the platform with which they can improve the performance, power consumption and feature sets of their next-generation SoCs.”
Rockchip has previously licensed multiple generations of CEVA DSPs and connectivity IPs, including RivieraWaves Bluetooth and Wi-Fi products. CEVA’s latest generation imaging and vision DSP, the CEVA-XM4, addresses the extreme processing requirements of the most sophisticated computational photography and computer vision applications such as video analytics, augmented reality and advanced driver assistance systems (ADAS). By offloading these performance-intensive tasks from the CPUs and GPUs, the highly-efficient DSP dramatically reduces the power consumption of the overall system, while providing complete flexibility. The platform includes a vector processor developed specifically to deal with the complexities of such applications and an extensive Application Development Kit (ADK) to enable easy development environment. The CEVA ADK includes an Android Multimedia Framework (AMF) that streamlines software development and integration effort, a set of advanced software development tools and a range of software products and libraries optimised for the DSP. For embedded systems targeting deep learning, the CEVA Deep Neural Network (CDNN2) real-time neural network software framework streamlines machine learning deployment at a fraction of the power consumption of the leading GPU-based systems.