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Publication:

AMUC: Associated Motion Capture User Categories (2009)

Author(s): Norman SJ, Lawson SEM, Olivier P, Watson P, Chan AMA, Dade-Robertson M, Dunphy P, Green D, Hiden H, Hook J, Jackson DG

    Abstract: The AMUC (Associated Motion capture User Categories) project consisted of building a prototype sketch retrieval client for exploring motion capture archives. High-dimensional datasets reflect the dynamic process of motion capture and comprise high-rate sampled data of a performer's joint angles; in response to multiple query criteria, these data can potentially yield different kinds of information. The AMUC prototype harnesses graphic input via an electronic tablet as a query mechanism, time and position signals obtained from the sketch being mapped to the properties of data streams stored in the motion capture repository. As well as proposing a pragmatic solution for exploring motion capture datasets, the project demonstrates the conceptual value of iterative prototyping in innovative interdisciplinary design. The AMUC team was composed of live performance practitioners and theorists conversant with a variety of movement techniques, bioengineers who recorded and processed motion data for integration into the retrieval tool, and computer scientists who designed and implemented the retrieval system and server architecture, scoped for Grid-based applications. Creative input on information system design and navigation, and digital image processing, underpinned implementation of the prototype, which has undergone preliminary trials with diverse users, allowing identification of rich potential development areas.

    Notes: Theme Issue ‘Crossing boundaries: computational science, e-Science and global e-Infrastructure II. Selected papers from the UK e-Science All Hands Meeting 2008’ compiled by P. V. Coveney and M. P. Atkinson.

      • Date: 13-07-2009
      • Journal: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
      • Volume: 367
      • Issue: 1898
      • Pages: 2771-2780
      • Publisher: The Royal Society Publishing
      • Publication type: Article
      • Bibliographic status: Published
      Staff

      Professor Paul Watson
      Professor of Computing Science