• DocumentCode
    2202825
  • Title

    Articulated body motion capture by annealed particle filtering

  • Author

    Deutscher, Jonathan ; Blake, Andrew ; Reid, Ian

  • Author_Institution
    Dept. of Eng. Sci., Oxford Univ., UK
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    126
  • Abstract
    The main challenge in articulated body motion tracking is the large number of degrees of freedom (around 30) to be recovered. Search algorithms, either deterministic or stochastic, that search such a space without constraint, fall foul of exponential computational complexity. One approach is to introduce constraints: either labelling using markers or colour coding, prior assumptions about motion trajectories or view restrictions. Another is to relax constraints arising from articulation, and track limbs as if their motions were independent. In contrast, we aim for general tracking without special preparation of objects or restrictive assumptions. The principal contribution of the paper is the development of a modified particle filter for search in high dimensional configuration spaces. It uses a continuation principle based on annealing to introduce the influence of narrow peaks in the fitness function, gradually. The new algorithm, termed annealed particle filtering, is shown to be capable of recovering full articulated body motion efficiently
  • Keywords
    biomechanics; filtering theory; motion estimation; optical tracking; search problems; simulated annealing; annealed particle filtering; annealing; articulated body motion capture; articulated body motion tracking; colour coding; continuation principle; exponential computational complexity; fitness function; full articulated body motion recovery; general tracking; high dimensional configuration spaces; modified particle filter; motion trajectories; narrow peaks; prior assumptions; search algorithms; view restrictions; Animation; Annealing; Application software; Biological system modeling; Computational complexity; Electrical capacitance tomography; Filtering; Humans; Legged locomotion; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2000. Proceedings. IEEE Conference on
  • Conference_Location
    Hilton Head Island, SC
  • ISSN
    1063-6919
  • Print_ISBN
    0-7695-0662-3
  • Type

    conf

  • DOI
    10.1109/CVPR.2000.854758
  • Filename
    854758