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Motion Data Beyond Animation

  • Author / Creator
    Salzvedel Furtado Junior, Antonio Carlos
  • Motion capture (MoCap) data has always been one of the most important components in the entertainment industry, being widely employed in animated movies and games. Given technological advancements in motion capture technologies, it has been successfully applied to other areas, such as surgical assessment, elderly monitoring and surveillance systems. As capture technologies are further developed, and human kinematic models are commonly employed in different fields, new issues regarding data optimization arise.In this thesis, we present novel methods that optimize the use of MoCap data in three distinct situations: unreliable network transmission, data compression and human identification. These methods assist MoCap-based applications outside the traditional animation scope, and become relevant as data format is standardized.

  • Subjects / Keywords
  • Graduation date
    2016-06
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R3F766J26
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Master's
  • Department
    • Department of Computing Science
  • Supervisor / co-supervisor and their department(s)
    • Cheng, Irene (Computing Science)
    • Basu, Anup (Computing Science)
  • Examining committee members and their departments
    • Basu, Anup (Computing Science)
    • Sander, Joerg (Computing Science)
    • Cheng, Irene (Computing Science)
    • Elmallah, Ehab (Computing Science)