• DocumentCode
    384249
  • Title

    Tracking multiple animals in wildlife footage

  • Author

    Tweed, David ; Calway, Andrew

  • Author_Institution
    Dept. of Comput. Sci., Bristol Univ., UK
  • Volume
    2
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    24
  • Abstract
    We describe a method for tracking animals in wildlife footage. It uses a CONDENSATION particle filtering frame-work driven by learnt characteristics of specific animals. The key contribution is a periodic model of animal motion based on the relative positions over time of trackable features at significant body points. We also introduce techniques for maintaining a multimodal state density within the particle filter over time to enable consistent tracking of multiple animals. Initial experiments show that the approach has considerable potential.
  • Keywords
    filtering theory; image motion analysis; image sequences; object detection; optical tracking; video signal processing; CONDENSATION particle filtering framework; animal characteristics; body points; multimodal state density; multiple animal tracking; periodic animal motion model; trackable features; video; wildlife footage; Animals; Computer science; Data mining; Focusing; Image sequences; Layout; Particle tracking; Probability distribution; Robustness; Wildlife;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2002. Proceedings. 16th International Conference on
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-1695-X
  • Type

    conf

  • DOI
    10.1109/ICPR.2002.1048227
  • Filename
    1048227