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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.

Gary Bradski, President and CEO of the OpenCV Foundation, delivers the keynote at the July 2012 Embedded Vision Alliance Member Meeting.

"Embedded vision" refers to the use of computer vision technology in embedded systems, i.e. systems that extract meaning from visual inputs.

Xilinx's Video Scaler/OSD reference designs allow the user to quickly evaluate and experiment with the Xilinx Video Scaler IP core.

Traffic sign recognition is one of emerging capabilities of advanced driver assistance and safety systems (Chinese language soundtrack).

Traffic sign recognition is one of emerging capabilities of advanced driver assistance and safety systems (English language soundtrack).

The CogniVue SmartEBC analyzes data from a single rear-view camera to track objects and perform feature detection and distance estimation.

CogniMem’s Chris McCormick, application engineer, demonstrates how pattern recognition can bring enhanced gestures to the Microsoft Kinect.

This demonstration pairs a Freescale i.MX board and CogniMem Technologies CM1K evaluation module and shows how to use your eyes as a mouse.

Making the automotive environment safer by reducing injuries and fatalities is always a hot topic of the automotive industry.

When a driver starts a car, he doesn’t think about starting an intelligent analytics system; sometimes, that’s precisely what he’s doing.