Embedded Vision Insights: January 15, 2013 Edition

Dear Colleague,

In the previous edition of Embedded Vision Insights, I mentioned that material from the December Alliance Member Summit was beginning to appear on the website. The content suite is now complete; videos published in the last several weeks include a fascinating keynote on machine learning by Professor Kristen Grauman of the University of Texas at Austin, and the technology trends presentation on embedded vision in mobile electronics, co-delivered by BDTI senior software engineer Eric Gregori and myself.

Also now on the site in video form is an interesting discussion that Embedded Vision Alliance Founder Jeff Bier held last month with Daniel Wilding, a digital hardware engineer at National Instruments, who hosted the Member Summit. Bier and Wilding discuss National Instruments' presence and plans in the embedded vision application space, the advantages of FPGAs as embedded vision processors, and the company's development tools for FPGA-based embedded vision designs.

I commend all of this compelling content to your attention. And with the December Alliance Member Summit material published, my attention has now fully turned to the upcoming April 25 Embedded Vision Summit in San Jose, California. As promised last time, online registration for this public event is now live on the website. Space is limited, and I therefore encourage you to submit your registration application right away in order to increase your likelihood of securing a spot in this one-of-a-kind event. In the coming weeks, I'll publish additional event information; a detailed agenda, for example, along with speaker biographies.

And speaking of conferences, last time I also mentioned that Jeff Bier and the Alliance's business director, Jeremy Giddings, would be attending the Consumer Electronics Show. I'm happy to report that both Jeff and Jeremy have survived their time in Las Vegas, and have returned with an abundance of good news regarding the burgeoning presence of embedded vision-based user interfaces (gesture, gaze, etc.) and other technologies in computers, televisions, game consoles, smartphones and tablets, and numerous other devices. Jeff and Jeremy shot several video demonstrations, which I'll get on the site as soon as possible, along with various news write-ups written by myself. Keep an eye out for them, and for now, check out the CES-related press releases published by various Alliance member companies.

Thanks as always for your support of the Embedded Vision Alliance, and for your interest in and contributions to embedded vision technologies, products and applications. And also as always, I welcome your feedback on how the Alliance can do a better job of servicing your needs.

Brian Dipert
Editor-In-Chief, Embedded Vision Alliance

December 2012 Embedded Vision Alliance Member Summit Keynote
Professor Kristen Grauman of the University of Texas at Austin presents the keynote on machine learning at the December 2012 Embedded Vision Alliance Member Summit. Machine learning is a type of artificial intelligence that provides systems with the ability to learn without being explicitly programmed. It focuses on the development of programs that can teach themselves to grow and change when exposed to new data, and is an essential part of many vision applications. Grauman's group at UT Austin focuses on problems in computer vision and machine learning, particularly visual recognition and large-scale image and video retrieval. The goal of their research is to develop algorithms to categorize and detect objects, activities, or scenes, and large-scale visual search techniques that can rapidly identify the most relevant content within massive collections. Grauman's presentation introduces key problems in machine learning for computer vision, and highlights recent work tackling those problems..

December 2012 Embedded Vision Alliance Member Summit Product Demonstration: videantis
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