• DocumentCode
    248421
  • Title

    Graph-based approach for motion capture data representation and analysis

  • Author

    Jiun-Yu Kao ; Ortega, Antonio ; Narayanan, Shrikanth S.

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    2061
  • Lastpage
    2065
  • Abstract
    Providing better representation methods for motion capture data can lead to improved performance in terms of classification, recognition, synthesis and dimensionality reduction. In this paper, we propose a novel representation method inspired by algebraic and spectral graph theoretic concepts. Our proposed method represents motion data in a space constructed with bases for skeleton-like graphs. We introduce two criteria and as well as its influences on the generated bases. With experiments on CMU MoCap database, we will also discuss how this method may act as a good preprocessing tool in order to enhance the further analysis steps on MoCap data.
  • Keywords
    data analysis; data reduction; data structures; graph theory; image motion analysis; CMU MoCap database; algebraic graph theoretic concept; dimensionality reduction; gait analysis; graph-based approach; motion capture data analysis; motion capture data representation; skeleton-like graphs; spectral graph theoretic concept; Databases; Joints; Laplace equations; Legged locomotion; Principal component analysis; Vectors; Human motion; dimensionality reduction; gait analysis; graph-based approach; motion capture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2014 IEEE International Conference on
  • Conference_Location
    Paris
  • Type

    conf

  • DOI
    10.1109/ICIP.2014.7025413
  • Filename
    7025413