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Avinash Nehemiah of MathWorks delivers a technical presentation at the May 2014 Embedded Vision Summit.

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The Embedded Vision Summit was held on May 29, 2014 in Santa Clara, California, as a technical educational forum for product creators.

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Today, virtually every tablet and smartphone is capable of sophisticated vision functions, used to enable new types of applications.

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Fast, low power processors and high resolution, high frame rate image sensors, along with powerful software, bring AR to the masses.

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Neil Trevett of Khronos delivers a presentation at the March 2014 Embedded Vision Alliance Member Meeting.

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OpenCV for Tegra is an optimized port of the OpenCV library. It runs on Android and has ~2500 image processing and computer vision functions

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Computer vision capabilities on embedded platforms are available to ADAS developers, including CUDA-based OpenCV and the OpenVX vision API.

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NVIDIA and Itseez have optimized many OpenCV functions using CUDA on NVIDIA GPUs. These functions are 5-100x faster than CPU counterparts.

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In this webinar from NVIDIA, learn how the OpenCV embedded vision algorithm library has been accelerated using CUDA on NVIDIA GPUs.

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ADAS is among the early success stories in the burgeoning embedded vision era, and its usage is rapidly expanding.

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