Rajkumar Kannan

  1. Topic Map: An Ontology Framework for Information Retrieval.

    Authors: Rajkumar Kannan
    Subjects: Digital Libraries
    Abstract

    The basic classification techniques for organizing information are thesauri,
    taxonomy and faceted classification. Topic map is relatively a new entrant to
    this information space. Topic map standard describes how complex relationships
    between abstract concepts and real world resources can be represented using XML
    syntax.

  2. Towards Automated Lecture Capture, Navigation and Delivery System for Web-Lecture on Demand.

    Authors: Rajkumar Kannan, Frederic Andres
    Subjects: Multimedia
    Abstract

    Institutions all over the world are continuously exploring ways to use ICT in
    improving teaching and learning effectiveness. The use of course web pages,
    discussion groups, bulletin boards, and e-mails have shown considerable impact
    on teaching and learning in significant ways, across all disciplines.

  3. Tutoring System for Dance Learning.

    Authors: Rajkumar Kannan, Frederic Andres, Balakrishnan Ramadoss
    Subjects: Information Retrieval
    Abstract

    Recent advances in hardware sophistication related to graphics display, audio
    and video devices made available a large number of multimedia and hypermedia
    applications. These multimedia applications need to store and retrieve the
    different forms of media like text, hypertext, graphics, still images,
    animations, audio and video. Dance is one of the important cultural forms of a
    nation and dance video is one such multimedia types. Archiving and retrieving
    the required semantics from these dance media collections is a crucial and
    demanding multimedia application.

  4. Semantic Modeling and Retrieval of Dance Video Annotations.

    Authors: Rajkumar Kannan, Balakrishnan Ramadoss
    Subjects: Multimedia
    Abstract

    Dance video is one of the important types of narrative videos with semantic
    rich content. This paper proposes a new meta model, Dance Video Content Model
    (DVCM) to represent the expressive semantics of the dance videos at multiple
    granularity levels. The DVCM is designed based on the concepts such as video,
    shot, segment, event and object, which are the components of MPEG-7 MDS. This
    paper introduces a new relationship type called Temporal Semantic Relationship
    to infer the semantic relationships between the dance video objects.

  5. Modeling and Annotating the Expressive Semantics of Dance Videos.

    Authors: Rajkumar Kannan, Balakrishnan Ramadoss
    Subjects: Multimedia
    Abstract

    Dance videos are interesting and semantics-intensive. At the same time, they
    are the complex type of videos compared to all other types such as sports, news
    and movie videos. In fact, dance video is the one which is less explored by the
    researchers across the globe. Dance videos exhibit rich semantics such as macro
    features and micro features and can be classified into several types. Hence,
    the conceptual modeling of the expressive semantics of the dance videos is very
    crucial and complex.

  6. Discovering Knowledge from Multi-modal Lecture Recordings.

    Authors: Rajkumar Kannan, Christian Guetl
    Subjects: Multimedia
    Abstract

    Educational media mining is the process of converting raw media data from
    educational systems to useful information that can be used to design learning
    systems, answer research questions and allow personalized learning experiences.
    Knowledge discovery encompasses a wide range of techniques ranging from
    database queries to more recent developments in machine learning and language
    technology. Educational media mining techniques are now being used in IT
    Services research worldwide.

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