resistance to packet losses. New scalable and distributed coding solutions promise to deliver all of this—and much more.
A pair of Swiss-based standards organizations, International Organization for Standardization and International Telecommunication Union (ITU), formed a Joint Video Team in 2001 to develop a network-friendly video standard. Completed in 2003 and subsequently refined, H.264/AVC (Advanced Video Coding) attained measurably superior performance over existing standards. With the uplink model in ascendancy, there is continuing development in two promising areas: scalable video coding (SVC), an extension of the H.264/AVC standard, and distributed video coding (DVC).
An example of video scalability is when a “server has this 20Mbps coded video and you have a connection that can deliver 10Mbps,” says Gary Sullivan, a video architect with Microsoft and chair of the ITU-T Video Coding Experts Group. “If the video is encoded in a scalable way, the server can take just the subset of the data that represents the lower quality and give you that.”
Video data is delivered in packets, and if the video is not coded in a scalable manner, there’s basically very little a person can do other than decode all of them, notes Sullivan. However, if the video is encoded in a scalable way, then some packets belong to the base layer and some packets belong to the enhancement layer. Sullivan muses that it’s possible create a bitstream with 10 layers, covering a wide range of decoders. “It’s a nice concept, but
has been difficult to achieve,” he says.
A professor at the Electrical and Computers Engineering Department at Portugal’s Instituto Superior Técnico and the chair of many ad hoc video standards groups, Fernando Pereira is trying to chart video’s course from scalable to distributed. Not only will there be the multiple layers from SVC, but the new distributed video encoding will dynamically divvy up the work between encoders and decoders.
Pereira likens progress in the field of video coding to paleontologist Stephen Jay Gould’s description of “ punctuated equilibrium” in evolution during which periods of stasis are interrupted by flurries of “creative destruction” and rapid change.
Video coding’s state of the art in
the early 1970s was represented by the Slepian-Wolf theorem that describes lossless coding—a way to reduce file sizes without losing any bits—with rather small compression factors. By 1976, Abraham Wyner and Jacob Ziv had derived the Wyner-Ziv theorem that essentially defines the conditions under which the picture quality can be achieved even when the coding process is not lossless.
Because it does not delete irrelevant information, the Slepian-Wolf theorem by itself has little practical application in video compression today. However, the Slepian-Wolf and Wyner-Ziv theorems together suggest the potential to compress two signals in a distributed way, with two separate encoders supplying a single joint decoder, says Pereira. He is confident this approach can achieve “a coding efficiency close to that of the predic-tive, joint encoding and decoding schemes” now in widespread use.
As opposed to conventional coding, in DVC the task of motion estimation is performed only on the decoder side to generate motion-compensated predictions for each input frame. The coding efficiency of a DVC scheme is judged to a great degree on the quality of these predictions.
The new DVC model promises substantial advantages for existing and emerging applications. They include flexible resources (DVC allocates varying amounts of encoder complexity to the decoder, which results in low encoder complexity and low battery consumption), improved resilience (DVC codecs do not rely on repetitive prediction loops, so channel in-
Today’s cubicle dweller switches gears every three minutes, moving from one task to anything else bombarding his or her attention. Indeed, the office environment has become such a breeding ground for interruptive technologies like emailing, cybersurfing, and IMing, that disruptions are now consuming as much as 28% of the average U. S. worker’s day and
sap productivity by as much as $650 billion a year, according to Manhattan-based business research firm Basex.
In response, a growing number of tools and technologies are emerging to help keep workers on task. Microsoft is working on some remedies for attention disruption disorder that include AI systems that observe humans at work and
build models that predict the cost and benefit of interrupting someone, Business Week reports. A prototype of an email triage program called Priorities ranks messages in order of perceived importance. The Outlook Mobile Manager enables Outlook to recognize urgent messages. And Bounded Deferral holds messages until a recipient is ready for a “cognitive break.”
IBM is also on the attention management track, now testing a prototype IM answering machine known as IMSavvy that can “sense” when a worker is too busy to answer calls or messages and will relay that sentiment to would-be interrupters. The system also offers a whisper option, flickering text on a worker’s screen even if the worker has instructed the system to withhold messages.
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