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Research Work on SMIL Group 5: SMIL Section 3 By: Nitin Bafna Group 5: SMIL Jason Burke Abha Gupta Nitin Bafna Disclaimer This document is created fully for a purpose of class study and will be removed from the internet after the semester.

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Research Work on SMIL

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research work on smil

Research Work on SMIL

Group 5: SMIL

Section 3

By: Nitin Bafna

Group 5: SMIL

Jason Burke

Abha Gupta

Nitin Bafna

  • This document is created fully for a purpose of class study and will be removed from the internet after the semester.
  • All material is taken from different references mentioned with each topic.
compression of smil documents http csdl computer org comp proceedings dcc 2000 0592 00 05920572 pdf
  • Data compression is a process to reduce the number of bits in a representation of data.
  • SMIL-lossless Compression
  • Cannot use methods like Lampel-Ziv – like English text(2-4 bits/char)
  • The proposed compression algorithm contains two major procedures:
    • parsing and
    • coding.
  • Parsing - to segment a SMIL document into non–overlapping phrases
  • Coding - assign a codeword to the phrase.
  • Hierarchical procedure:
  • Parse a SMIL document into elements.
  • Parse an empty element into (1) ’<’ and element name, (2) attributes and (3) ’/>’. If some attributes are required attributes merge them with (1).
  • Parse a non–empty element into (1) STag, (2) child elements and (3) ETag.
  • Parse a STag into (1) ’<’ and element name, (2) attributes and (3) ’>’.
  • Parse an attribute into (1) attribute name and ’=’, and (2) AttValues.
  • Parse an AttValue into phrases or symbols. For instance, the AttValue of ”src” is segmented into (1) protocol name (e.g. http://www. or rtsp://www.), (2) a string of alphnumerals and (3) extension (e.g. .html or .jpg).
  • After parsing, a variable–length code is assigned to each phrase based on the conditional probability.
  • The performance is 400%–600% better than other commercial compression methods, such as COMPRESS and GZIP.
Modeling and Analyzing SMIL Documents in SAM
  • This paper proposes a formal approach to modeling and analyzing temporal aspects of SMIL documents using the Software Architecture Model (SAM)

Linear-time temporal logic

Clocked transition system

Stanford Temporal prover

  • Dr. soon Chunk also explained the method of modeling SMIL elements using PtNRS
order and reliability in smil documents http portal acm org citation cfm id 837373
Order and Reliability in SMIL Documents
  • This research shows some differences existing between SMIL and REMDOR (REmote Multimedia DOcuments Retrieval) temporal models and looks at how the order and reliability concepts of REMDOR can be expressed within SMIL.
  • REMDOR - developed by the PEL group to show the benefits of a PO/PR transport service for multimedia document retrieval over the Internet
  • Differences in SMIL and REMDOR temporal models

One possible solution:

Introducing Strong and weak Par element ie.spar and wpar

Otherwise by defining new attribute in par element

TANDEMTransmitting Asynchronous Non Deterministic andDeterministic Events in Multimedia Systems over the Internet
  • Limitation of SMIL
    • does not support frame level synchronization due to the lack of synchronization of periodic signals.
    • SMIL also does not support nondeterministic order of events and partial matching of conditions.
  • TANDEM – XML based language:
    • The language allows the integration of asynchronous events, deterministic multimedia events, and multimedia event based triggering commands.
    • The language supports temporal and spatial synchronization of the complex media objects.
    • The language separates and integrates five major components of distributed multimedia reactive systems: triggers, active repository, transformers, grouping of media streams, and synchronization.
    • The language allows dynamic scaling of the multimedia time base for implicit synchronization
    • The language incorporates commands that interrogate the active repository for partial conditions verification as well as pattern detection, oblivious data and context-based conditions.
  • Dr. Beckham also tried to overcome this disadvantage of SMIL by developing language Rex which can be used with SMIL.
x smil browser http lib hut fi diss 2003 isbn9512268043 article6 pdf
  • The most popular browsers don’t support SMIL in its full, which slows down the utilization of SMIL.
  • The most common solution to use continuous media in WWW browsers is to utilize so called plug-ins.
  • The X-Smiles browser is a Java based browser, which supports, e.g., SVG, XForms, and Extensible Stylesheet Language Formatting Objects (XSLFO) in addition to SMIL.
  • Thus, it’s an ideal environment to experiment with SMIL and related XML specifications.
  • Technical issues in Implementation of the SMIL MLFC:
    • Having an abstract representation of the source document in the form of a DOM tree, how should one convert this representation into a run-time SMIL presentation?
    • JMF supports only streaming media, such as video and audio. How should JMF be extended to support static media types such as images and text?
    • How should timing and synchronization issues be solved?
    • How the SMIL MLFC can interact with other MLFCs?
  • SMIL is proved to be evolution in multimedia languages
  • Still we need a browser / player which will be compatible for all extra extensions have been researched till now.