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Imagineering Creative Technologies

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Title: Imagineering Creative Technologies


1
Imagineering Creative Technologies
  • Professor Paul Mc Kevitt
  • Intelligent Systems Research Centre
  • School of Computing Intelligent Systems
  • Faculty of Computing Engineering
  • University of Ulster, Magee
  • Derry/Londonderry
  • Northern Ireland

2
Background
  • Intelligent MultiMedia MultiModal Systems
  • Integration of natural language, speech/audio,
    graphics/VR, vision
  • Semantic representation, fusion synchronisation
  • Affective computing
  • Integration reuse of existing software
    (Thórisson, 2007)
  • Relations with cognitive science
  • Deployment on mobile devices
  • (Dell Axim, Smartphones, Nintendo DS)
  • Applications in arts music, drama, dance,
    design, computer games, film, TV/radio, art,
    storytelling

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CHAMELEONa platform for developing intelligent
multimedia applications
  • Tom Brøndsted, Paul Dalsgaard, Lars Bo Larsen,
  • Mike Manthey, Paul Mc Kevitt
  • (CPK, Aalborg University, Denmark)
  • Speech input/output, image processing laser
  • IntelliMedia Workbench campus information system
    application
  • Semantic representation with frames (Minsky,
    1975)
  • Blackboard for semantic representation
  • Bielefeld DACS distributed communications
    platform (Fink et al., 1996)
  • Implemented with C, C, DACS, Infovox TTS,
    grapHvite
  • Applications in multimodal systems development

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Architecture of CHAMELEON
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IntelliMedia Workbench
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CHAMELEON Semantic Representation
  • Semantic Frames (Minsky, 1975)

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CONFUCIUSautomatic conversion of natural
language to 3D animation
  • Minhua (Eunice) Ma, Paul Mc Kevitt
  • Lexical Visual Semantic Representation (LVSR)Use
    of Jackendoffs (1990) Lexical Conceptual
    Structure (LCS)
  • Schanks (1977) scripts
  • Use of Fellbaums (1998) semantic classes in
    WordNet
  • Implementation with Java, VRML, WordNet, Connexor
    parser, FreeTTS (Java)
  • Applications in education, computer games,
    animation production,
  • digital storytelling

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Architecture of CONFUCIUS
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MultiModal semantic representation
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CONFUCIUS examples
  • Contact verb example
  • (e.g. hit, collide, scratch, touch)
  • The car collided with a wall.
  • Collision detection
  • Nonspeech sound effects
  • No human role involved
  • Human action verb examples
  • Ipke gave Brigitte a loaf of bread.
  • Bernie put a cup of coffee on the table.
  • H-Anim Site node
  • locative tags of object
  • (on tag for table object)
  • Paul pushed the door.
  • Gert ate the bread.

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Paul sat on the chair. Teri was waving
goodbye. Helge went to the gym. Gert put on
his hat. States Anke is sad. Anke is
ashamed.
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SceneMakerautomatic visualisation of
screenplays
  • Eva Hanser, Joan Condell, Tom Lunney, Paul Mc
    Kevitt
  • Automatically generates affective virtual scenes
    from screenplays/play scripts
  • Realistic visualisation of emotional aspects
  • Extraction of genre/moods from screenplays
  • Use of OCC (Ortony-Clore-Collins) affective
    model,
  • ConceptNet, Open Mind Common Sense (OMCS),
    WordNet-Affect
  • Enhance believability of virtual actors and scene
    presentation
  • Multimodal representation with 3D animation,
    speech,
  • audio cinematography
  • Applications in assisting directors, actors,
    drama students, scriptwriters

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Architecture of SceneMaker
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MemoryLanea mobile digital storytelling
companion
  • Sheila Mc Carthy, Heather Sayers, Mike McTear,
    Paul Mc Kevitt
  • Multimodal stories (speech, text, video) from
    life-cached
  • memory data (poems, songs, photos, home videos)
  • Extensive HCI requirements analysis with focus on
    older people
  • Multimodal preferences and abilities of users
    determines
  • story modalities and user interface
    configuration
  • Prudent on sensitive life-cached data
  • Creates new stories on the fly
  • Applications in medical informatics and digital
    care
  • Implemented with Microsoft Visual Studio
  • Deployed on Dell Axim X51v PDA

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Architecture of MemoryLane
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MemoryLane Prototype
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AmbiLearnan ambient intelligent multimodal
learning environment for children
  • Jennifer Hyndman, Tom Lunney, Paul Mc Kevitt
  • Educational games virtual learning environments
  • Child - Computer Interaction (ChiCI)
  • AmbiLearn architecture TreasureLearn
    application
  • Implementation with DevKit Pro (Nintendo
    homebrew)
  • Deployment on mobile device (Nintendo DS)
  • Application to collaborative learning for children

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Architecture of AmbiLearn
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PlayPhysicsan emotional games learning
environment for teaching Physics
  • Karla Munoz Esquivel, Tom Lunney, Paul Mc Kevitt
  • Virtual Learning Environment (VLE) for teaching
    Physics
  • Incorporating serious games intelligent
    tutoring systems (ITS)
  • Modelling of emotions personality of student
  • Use of Bayesian Networks for modelling student
    knowledge
  • Affective feedback through audio-visual effects
  • On-line web application with Student, Lecturer,
  • Head of Department, Administrator views
  • Implemented with Elvira Bayesian Network tool,
    Flash, Java, Tomcat Apache Server, MySQL
    database, ConceptNet, 3D Studio Max Maya
  • Applications in educational software computer
    games

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Olympia architecture
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PlayPhysics interface (astronaut game)
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TeleMorph TeleTurasbandwidth determined
mobile multimodal presentation
  • Tony Solon, Kevin Curran, Paul Mc Kevitt
  • Multimedia limitations of mobile networks,
  • mobile device capabilities
  • User preferences on modalities
  • Transmoding between modalities with
    cross-modality adaptation
  • Use of Fuzzy (logic) Inference system (FIS)
  • TeleMorph platform TeleTuras tourist
    application
  • Implemented with MATLAB
  • Applications in streaming media, computer
    networks,
  • multimodal presentation

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Architecture of TeleMorph Fuzzy Inference System
(FIS)
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TeleTuras GUI
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Available media qualities in 6 sample test
scenarios
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Adaptation trace data from test scenario 6
34
MediaHubBayesian decision-making in an
intelligent multimedia distributed platform hub
  • Glenn Campbell, Tom Lunney, Aiden McCaughey, Paul
    Mc Kevitt
  • Interpret/generate semantic representations of
    multimodal input/output
  • Fusion synchronisation of multimodal data
  • Decision-making with Bayesian
    Causal Probabilistic
    Networks (CPNs)
  • Implemented with Psyclone platform,
    HuginLite Bayesian modelling
    tool, Java, NetBeans IDE
  • Applications in decision-making for key problems
    in
  • multimodal systems
    anaphora resolution,
    domain knowledge awareness, multimodal
    presentation, turn-taking, dialogue-act
    recognition parametric learning

35
Architecture of MediaHub
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Decision-making layers
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psyProbe view of MediaHub Whiteboard
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Alternative Turn-taking' Bayesian network in
Hugin
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SoFISOng Form Intelligence for repairing
streaming musicacross wireless bursty networks
  • Jonathan Doherty, Kevin Curran, Paul Mc Kevitt
  • Large packet loss dropouts of 5 - 15 s.
  • Use audio pattern recognition matching to
    repair gaps
  • K-means clustering classifier determines
    self-similarity matches
  • Match current sections of song received with
    previous
  • sections played
  • Typicality of Western Tonal Format (WTF)
  • Use of MPEG-7 Audio Spectrum Envelope (ASE)
    multimedia content description standard giving
    features for extraction
  • Implemented with G-streamer for steaming media,
    Ices2, Icecast2 for audio broadcast MPEG-7
    Audio Spectrum Envelope (ASE)
  • Applications in repair of streaming music

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Architecture of SoFI
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Spectrogram representation
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Steganoflagestrengthening steganography in
digital images
  • Abbas Cheddad, Joan Condell, Kevin Curran, Paul
    Mc Kevitt
  • Hiding/embedding data in transmission medium
  • Use of 1D hash algorIthm coupled with
    2D iFFT (irreversible
    Fast Fourier Transform)
  • Encryption of digital documents in 2D spatial
    domain
  • Use of steganography to add security layer
    resistant to
  • noise JPEG compression
  • Exploitation of Jarvis kernel (Jarvis et al.,
    1976) to generate error diffusion signal
  • Use of Wavelet-based Inverse Halftoning via
    De-convolution (WInHD) to recover approximate
    original signal
  • Implemented with MATLAB PHP
  • Applications in security, forensics, forgery,
    digital watermarking

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Architecture of Steganoflage
46
Securing confidential data
Application
The traditional method of securing individuals
data with the notion of security by obscurity
that Steganography introduces
47
National international collaboration
  • InstitutoTecnológico de Estudios Superiores de
    Monterrey, Campus Ciudad de México
    (ITESM-CCM), Mexico
  • Aalborg University, Denmark
  • CADIA, Reykjavik University, Iceland
  • University of Bielefeld, Germany
  • LIMSI (CNRS), Orsay, Paris, France
  • Sheffield University, England
  • Stanford University, California, USA

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Noel Sharkey thinks AI is an illusion
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Intellectural Property (IP)
  • Steganoflage
  • United Kingdom Patent Application No.
    0819982.0
  • Method for Skin Tone Detection,
  • University of Ulster,
  • Abbas Cheddad, Joan Condell, Kevin Curran, Paul
    Mc Kevitt.
  • SoFI
  • United Kingdom Patent Application No.
    0908879.0
  • A system and method for streaming music repair
    and error concealment,
  • University of Ulster,
  • Jonathan Doherty, Kevin Curran, Paul Mc Kevitt.

53
Industrial collaboration
  • InterTradeIreland Fusion project, 2008/10
  • Nvolve Ltd., Letterkenny, Co. Donegal, Ireland,
  • Michael McNeill,
  • School of Computing Information Engineering,
    Coleraine
  • Prof. Paul Mc Kevitt.
  • Enterprise Ireland Innovation Voucher, IV-2008
    1047, 2008/09
  • Navigatour'',
  • Backseat Tour Guides Ltd., Letterkenny, Co.
    Donegal, Ireland,
  • Anton Hutton, School of Creative Arts EyeSpyFX
  • Prof. Paul Mc Kevitt.

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  • University of Ulster, Office of Innovation,
  • Proof-of-Principle (PoP), 2008/09
  • Identity cards employing steganography,
  • Abbas Cheddad, Joan Condell, Kevin Curran, Paul
    Mc Kevitt.
  • University of Ulster, Office of Innovation,
  • Proof-of-Principle (PoP), 2009
  • System and method for streaming music repair
  • and error concealment,
  • Jonathan Doherty, Kevin Curran, Paul Mc Kevitt.
  • Invest NI Proof-of-Concept (PoC) project,
    2009/10
  • Secure digital watermarks (SDW)
  • secure data hiding in image frames using
    steganography,
  • Joan Condell, Kevin Curran, Paul Mc Kevitt.

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Creative People
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Conclusion future work
  • Imagineering creative technologies
  • MultiModal semantic representation
  • Affective computing
  • Deployment on mobile devices
  • Applications in creative industries
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