NTT, BayTSP Begin Joint Field Trial of NTT’s Robust Media Search Technology on BayTSP’s Content Authentication Platform

Reuters Mon Apr 21, 2008 10:00pm EDT
http://www.reuters.com/article/pressRelease/idUS28851+22-Apr-2008+BW20080422

NTT’s content recognition engine will be deployed in the U.S. for the first time combined with BayTSP’s Content Authentication Platform to enable content owners to monitor and manage how their intellectual property is used online.

The combination of NTT and BayTSP’s technologies will allow content owners to use proven video and audio fingerprinting technologies to monitor and manage how their intellectual property is used online, primarily on user-generated content sites like YouTube, Daily Motion, Google Video and Yahoo Video.

NTT has been researching and developing media search based on proprietary audio and video fingerprinting technologies since 1996.  The newly announced field trial in collaboration with BayTSP is the first application of NTT’s most advanced third generation robust media search technology to Internet content authentication applications on a large scale, and the first deployment of NTT’s Robust Media Search systems in the United States.
Relevant lecture:

8 CLASSIFICATION

16 CONETENT MANAGEMENT

18 METADATA FOR MULTIMEDIA

27 MULTIMEDIA IR

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Lines and Bubbles and Bars, Oh My!

New York Times, Aug. 30, 2008
http://www.nytimes.com/2008/08/31/technology/31novel.html?_r=1&ref=technology&oref=slogin

Many Eyes is a web service much like YouTube and Flickr, only instead of being able to share and tag photos, users can create, share, and tag visualizations of data. The tools used to generate graphical displays of data organization range from text clouds highlighting words most frequently used in a document or speech to creating more traditional circle and bar graphs, but the coolest part is how users are able to discuss the data and representation of the data in comments and how they can post their data representations to their own blogs or websites.

The part that struck me most in the article was the example of how a discussion in the comments lead to the data in question being represented in a different way, thereby leading to a slightly different conclusion.

Relevant lectures: Classification; Documents and Data Models… and Modeling; Social/Distributed Categorization

And as a bonus link incorporating cool data visualization: Debunking myths about the “Third World”

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