• DocumentCode
    2464315
  • Title

    Finite-Element Level-Set Curve Particles

  • Author

    Jiang, Tingting ; Tomasi, Carlo

  • Author_Institution
    Duke Univ. Durham, Durham
  • fYear
    2007
  • fDate
    14-21 Oct. 2007
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Particle filters encode a time-evolving probability density by maintaining a random sample from it. Level sets represent closed curves as zero crossings of functions of two variables. The combination of level sets and particle filters presents many conceptual advantages when tracking uncertain, evolving boundaries over time, but the cost of combining these two ideas seems prima facie prohibitive. A previous publication showed that a large number of virtual level set particles can be tracked with a logarithmic amount of work for propagation and update. We now make level- set curve particles more efficient by borrowing ideas from the Finite Element Method (FEM). This improves level-set curve particles in both running time (by a constant factor) and accuracy of the results.
  • Keywords
    edge detection; finite element analysis; particle filtering (numerical methods); probability; finite element method; finite-element level-set curve particles; particle filters; random sample; time-evolving probability density; zero crossings; Animals; Clouds; Encoding; Finite element methods; Level set; Particle filters; Particle measurements; Particle tracking; Shape measurement; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
  • Conference_Location
    Rio de Janeiro
  • ISSN
    1550-5499
  • Print_ISBN
    978-1-4244-1630-1
  • Electronic_ISBN
    1550-5499
  • Type

    conf

  • DOI
    10.1109/ICCV.2007.4409184
  • Filename
    4409184