A new computer vision (CV) software library has been launched for the development of "vision-enabled" applications targeting the mobile, home, PC, and automotive markets.
- The People Problem: Cyber Threats Aren't Just a Technology Challenge
- Coding to standards and quality: supply-chain application development
- Architecting Private and Hybrid Cloud Solutions: Best Practices Revealed
- How to Stop Web Application Attacks
Built by CEVA Inc, the new library is optimized for the firm's own CEVA-MM3101 imaging and vision platform. This is positioned as a tool for application developers to add vision capabilities to System-on-Chip (SoC) systems incorporating the CEVA-MM3101.
NOTE: So-called "vision enabled" applications can be found in areas such as wireless (or wired) sensor networks, mobile computing scanning apps, PCs, smart TVs, natural user interface (NUI) devices, and advanced driver assistance systems (ADAS).
CEVA-CV is based on OpenCV, a standard library of programming functions for computer vision processing. It includes more than 500 of the most frequently used computer vision functions — it also contains key CV kernels and algorithms required for application developers in this space.
These functions include both simple CV kernels such as filters, histogram, and affine transform as well as sophisticated CV algorithms including FAST, RANSAC, Connected Components, and MSER. The complete set of libraries has been fully optimized using CEVA's C-level compiler for the CEVA-MM3101 imaging and vision platform. This significantly shortens development time and simplifies the development process by eliminating the need for the programmer to understand the processor architecture, allowing them to develop in high-level languages.
"The introduction of the CEVA-CV computer vision libraries is the result of more than 100 man years of engineering invested in developing computer vision platforms and applications," said Eran Briman, vice president of marketing at CEVA.
"Together with our partners and customers in this rapidly developing technology field, we identified more than 500 of the most critical functions to support, and adapted these to ensure maximum power efficiency in embedded applications. Computer vision software programmers can easily add these functions to any CEVA-MM3101 enabled SoC and leverage the CEVA-MM3101 vector processor engine and C-level compiler to enable outstanding performance for their target application," added Briman.
Jeff Bier, founder of the Embedded Vision Alliance, suggests that the addition of CEVA's OpenCV-based computer vision libraries to the CEVA-MM3101 imaging and vision platform is a "significant step forward" for the development of embedded vision applications.
"Embedded vision applications are diverse and performance-hungry. By providing a large library of optimized software building blocks, CEVA is enabling application developers to more easily create embedded vision applications on SoCs based on the CEVA-MM3101. I commend CEVA on this exciting and important development in their computer vision roadmap," said Bier.
The CEVA-MM3101 is a fully programmable platform. By off-loading the device's main CPU and replacing multiple hardwired accelerators for performance-intensive imaging and vision processing tasks, the CEVA-MM3101 reduces the power consumption of the overall system, while providing complete flexibility.
NOTE: Target applications for the CEVA-MM3101 include advanced image enhancement applications (super resolution, HDR, and video stabilizer), NUI applications (gesture recognition, face recognition, and gaze detection), ADAS applications (forward collision warning – FCW, lane departure warning – LDW, and pedestrian detection – PD), computational photography, and video analytics.