• DocumentCode
    353945
  • Title

    Random sets in data fusion: formalism to new algorithms

  • Author

    Mori, Shozo

  • Author_Institution
    Inf. Extraction & Transp. Inc., Arlington, VA, USA
  • Volume
    1
  • fYear
    2000
  • fDate
    10-13 July 2000
  • Abstract
    Although a connection between multi-object tracking and random set theory was recognized during the course of the development of multi-hypothesis tracking algorithms, it was only recently that such a connection started to be discussed based on random set theory and to be related to several algorithms based on it. This paper describes a random set formalism of a general theory of multiple object tracking, and discusses recent developments in both theory and applications in an attempt to explore further applications of random set theory to data fusion.
  • Keywords
    random processes; sensor fusion; set theory; state estimation; tracking; algorithms; data fusion; multi-hypothesis tracking algorithms; multiple object tracking; random set theory; Chaos; Data mining; Density functional theory; History; Probability distribution; Random sequences; Set theory; State estimation; State-space methods; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Fusion, 2000. FUSION 2000. Proceedings of the Third International Conference on
  • Conference_Location
    Paris, France
  • Print_ISBN
    2-7257-0000-0
  • Type

    conf

  • DOI
    10.1109/IFIC.2000.862690
  • Filename
    862690