Inuitive selects CEVA-XM4 Intelligent Vision DSP

In addition, developers and OEMs will be able to leverage the open, programmable nature of the CEVA-XM4 in the Inuitive SoC to add their own differentiating features and algorithms via software, including their own neural networks which can be implemented via the CEVA Deep Neural Network (CDNN) framework.

"Inuitive is proud to collaborate with CEVA to develop cutting edge intelligent vision systems, that will form the foundation of mass-market visually aware mobile devices,” said Shlomo Gadot, co-founder & CEO at Inuitive. “The CEVA-XM4 delivers the best performance and power efficiencies in the market and provides the software infrastructures by which product builders can add their own algorithms and introduce revolutionary applications for vision-based systems.”

The NU4000 SoC builds on the success of Inuitive’s NU3000 multi-core image processor which utilised the third-generation CEVA-MM3101 imaging and vision DSP for stereoscopic vision. NU3000 serves as part of the Google Project Tango ecosystem, where developers can utilise it to power applications requiring real-time depth generation, mapping, localisation, navigation and other complex signal processing algorithms.

“We are delighted to extend our close relationship with Inuitive as they continue to innovate in the areas of 3D computer vision and image processing,” said Eran Briman, Vice President of marketing, CEVA. “Our CEVA-XM4 intelligent vision DSP delivers the power-efficiency and the flexibility that allows Inuitive and its customers implement a range of advanced machine-vision technologies on any mobile device, from neural network-based systems to highly-accurate depth sensing.”

CEVA’s imaging and vision DSPs 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 (CDNN) real-time neural network software framework streamlines machine learning deployment at a fraction of the power consumption of the leading GPU-based systems.