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MediaHub: An Intelligent Multimedia Distributed Hub

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Title: MediaHub: An Intelligent Multimedia Distributed Hub


1
MediaHub An Intelligent Multimedia Distributed
Hub
IntelliMedia
  • Student Glenn Campbell
  • Supervisors Dr. Tom Lunney
  • Prof. Paul Mc Kevitt
  • School of Computing and Intelligent Systems
  • Faculty of Engineering
  • University of Ulster, Magee

2
Project goals
  • The primary objectives of this research are to
  • Interpret/generate semantic representations of
    multimodal input/output
  •  
  • Perform decision-making (fusion and
    synchronisation) over multimodal data
  •  
  •  Implement MediaHub, a multimodal platform hub
  •  

3
Project objectives
  • Focus on following research questions
  • Will MediaHub use frames for semantic
    representation or XML or one of its derivatives?
  • How will MediaHub communicate with various
    elements of a platform?
  • Will MediaHub constitute a blackboard or
    non-blackboard model?
  • What mechanism will be implemented for
    decision-making within MediaHub?

4
Key research problems
  • Semantic Representation
  • Represent language and vision
  • Frames or XML?
  • Semantic Storage
  • Blackboard model?
  • Non-blackboard model?
  • Decision-making
  • Fusion and synchronisation
  • AI technique

5

Semantic representation
  • Frames (CHAMELEON)
  • MODULE
  • INPUT input
  • INTENTION intention-type
  • TIME timestamp
  •  
  • SPEECH-RECOGNISER
  • UTTERANCE(Point to Hannes office)
  • INTENTION instruction!
  • TIME timestamp
  •  
  • GESTURE
  • GESTURE coordinates (3, 2)
  • INTENTION pointing
  • TIME timestamp
  • XML (M3L, SmartKom)
  • ltpresentationTaskgt
  • ltpresentationGoalgt
  • ltinformgt ltinformFocusgt ltRealizationTypegtlist
    lt/RealizationTypegt lt/informFocusgt lt/informgt
  • ltabstractPresentationContentgt
  • ltdiscourseTopicgt ltgoalgtepg_browselt/goalgt
    lt/discourseTopicgt
  • ltinformationSearch id"dim24"gtlttvProgram
    id"dim23"gt
  • ltbroadcastgtlttimeDeictic id"dim16"gtnowlt/timeDei
    cticgt
  • ltbetweengt2003-03-20T194232
    2003-03-20T220000lt/betweengt
  • ltchannelgtltchannel id"dim13"/gt lt/channelgt
  • lt/broadcastgtlt/tvProgramgt
  • lt/informationSearchgt
  • ltresultgt lteventgt
  • ltpieceOfInformationgt
  • lttvProgram id"ap_3"gt
  • ltbroadcastgt ltbeginTimegt2003-03-20T195000lt/beginT
    imegt
  • ltendTimegt2003-03-20T195500lt/endTimegt
  • ltavMediumgt lttitlegtTodays Stock
    Newslt/titlegtlt/avMediumgt

6
Semantic storage
  • Blackboard or Non-blackboard?
  • High coupling Blackboard?
  • Low coupling - distributed architecture?
  • Communication
  • Via central blackboard?
  • Message passing between modules?

7
Decision-making (fusion synchronisation)
  • Rule-based
  • Potential for Other AI techniques
  • Fuzzy Logic
  • Neural Networks
  • Genetic Algorithms
  • Bayesian Networks (CPNs)

8
Distributed processing
  • PVM (Parallel Virtual Machine)
  • (Sunderam 1990, Fink et al. 1995)
  • ICE (Amtrup 1995)
  • DACS (Fink et al. 1995, 1996)
  • Open Agent Architecture (OAA)
  • (Cheyer et al. 1998, OAA 2004)
  • JATLite (Kristensen 2001, Jeon et al. 2000)
  • JavaSpaces (Freeman 2004)
  • CORBA (Vinoski 1993)

9
Intelligent Multimedia Distributed Platforms
  • Blackboard Model
  • Ymir (Thórisson 1999)
  • CHAMELEON (Brøndsted et al. 1998, 2001)
  • Smartkom
  • (Bühler et al. 2002, Wahlster et al. 2001,
    SmartKom 2004)
  • DARBS (Nolle et al. 2001)
  • DARPA Galaxy Communicator (Bayer et al. 2001)
  • Psyclone (Psyclone 2004)
  • Spoken Image/SONAS
  • (Ó Nualláin et al. 1994, Ó Nualláin Smith
    1994,
  • Kelleher et al. 2000)

10
Intelligent Multimedia Distributed Platforms
  • Non-blackboard Model
  • WAXHOLM (Carlson et al. 1996)
  • AESOPWORLD (Okada 1996)
  • COLLAGEN (Rich et al. 1997)
  • INTERACT (Waibel et al. 1996)
  • Oxygen (Oxygen 2004)
  • EMBASSI (Kirste 2001, EMBASSI 2004)
  • MIAMM (MIAMM 2004)

11
CHAMELEON
  • Language vision integration system
  • consists of ten modules, mostly programmed in C
    and C
  • DACS communication system used for communication
  • Blackboard stores semantic representations
    produced by other modules
  • Communication between modules achieved by
    exchanging semantic representations between
    themselves or blackboard
  • Semantic representation in form of input, output
    and integration frames

12
Architecture of CHAMELEON
13
SmartKom
  • User adaptive interface for human-computer
    interaction
  • Mobile
  • Public
  • Home/Office
  • Facilitates speech, gestures and facial
    expression input
  • XML-based mark-up language, M3L, used for
    semantic representation
  • Distributed multiple blackboard model

14
Architecture of SmartKom
15
Project proposal
  • Dialogue Manager
  • Acts as a blackboard module
  • Facilitates communication between other modules
  • Synchronisation
  • Semantic Representation Database
  • Provides semantic representation of language and
    vision data
  • Decision Making Module
  • AI technique for a unique form of decision-making
  • Bayesian Networks (CPNs)
  • Neural Networks, Genetic Algorithms, Fuzzy Logic

16
Architecture of MediaHub
17
Comparison of Intelligent MultiMedia Platforms
18
Software Analysis
  • Main Programming Language
  • Java
  • C
  • Semantic Representation
  • XML
  • XHTML Voice
  • SMIL
  • RDF Schema
  • MPEG-7
  • Decision Making
  • HUGIN (Bayesian Networks) (Hugin 2004)
  • FuzzyJ Toolkit (Fuzzy Logic) (NRC 2004)

19
Project Schedule
20
Conclusion
  • An intelligent multimodal distributed platform
    hub called MediaHub will be developed
  • MediaHub will interpret and generate semantic
    representations of multimodal input and output
  • MediaHub will perform fusion and synchronisation
    of language and vision data
  • Unique contribution of MediaHub is to provide a
    new method of decision making
  • MediaHub will be tested within an existing
    multimodal platform (e.g. CONFUCIUS)
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