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CEVA improves Android computer vision real-time library

24 Feb 2014  | Nick Flaherty

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CEVA has announced that it has included more than 250 functions to its CEVA-CV computer vision real-time library for Android processors. Together with the CEVA-CV computer vision library and CEVA's Android Multimedia Framework (AMF), the integration of CEVA-CV functions with any Android-based application processor for mobile, automotive, surveillance and consumer applications and the Internet of Things has now been made easier, stated the firm.

This, in turn, significantly increases performance and substantially lowers the power consumption of CV-enabled devices by offloading all computer vision processing from the CPU or GPU.

Recent functions added in the latest CEVA-CV release include feature detection kernels and object recognition algorithms such as Harris Corner, Hough Transform, Integral Sum, Fast, LBP, SURF, HOG, SVM, and ORB detection and matching. These are commonly used in augmented reality applications for smartphones, tablets, wearable devices, natural user interface (NUI), surveillance and advanced driver assistance systems (ADAS) applications. New optical flow kernels include KLT and Block Matching, which are used for motion detection and object tracking required in camera-enabled devices to implement applications such as digital video stabilization, augmented reality and gesture recognition. CEVA-CV now also includes kernels required by The Khronos Group's OpenVX 1.0 specification, which is set to become the key standard for cross-platform acceleration of computer vision applications and libraries. This brings the number of functions in the library up to 750.

- Nick Flaherty
  EE Times Europe

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