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The Embedded Vision Academy is a free online training facility for embedded vision product developers. This program provides educational and other resources to help engineers integrate visual intelligence―the ability of electronic systems to see and understand their environments―into next-generation embedded and consumer devices.

The goal of the Academy is to make it possible for engineers worldwide to gain the skills needed for embedded vision product and application development. Course material in the Embedded Vision Academy spans a wide range of vision-related subjects, from basic vision algorithms to image pre-processing, image sensor interfaces, and software development techniques and tools such as OpenCV. Courses will incorporate training videos, interviews, demonstrations, downloadable code, and other developer resources―all oriented towards developing embedded vision products.

The Embedded Vision Alliance™ plans to continuously expand the curriculum of the Embedded Vision Academy, so engineers will be able to return to the site on an ongoing basis for new courses and resources. The listing below showcases the most recently published Embedded Vision Academy content. Reference the links on the right side of this page to access the full suite of embedded vision content, sorted by technology, application, function, viewer experience level, provider, and type.

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

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

Larry Matthies of NASA delivers a presentation at the March 2014 Embedded Vision Alliance Member Meeting.

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

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

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

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

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

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

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