• DocumentCode
    424072
  • Title

    An improved data assignment solution for ML-based relaxation approach for multitarget tracking problem

  • Author

    Chen, Lung ; Hua, Qiang ; Li, Iao-Hong

  • Author_Institution
    Dept. of Comput. Sci., Northern British Columbia Univ., Vancouver, BC, Canada
  • Volume
    3
  • fYear
    2004
  • fDate
    26-29 Aug. 2004
  • Firstpage
    1361
  • Abstract
    It is proved that the optimal solution for the matching problem in multi-target tracking can be found from among n different matching. We show in this paper by simulation that the costs of the n different possible solutions constitute a bimodal sequence, which suggests an algorithm of O(N logN) complexity, lower than most of known algorithms.
  • Keywords
    computational complexity; maximum likelihood sequence estimation; pattern matching; relaxation theory; target tracking; O(N logN) complexity algorithm; bimodal sequence; data assignment solution; maximum likelihood based relaxation method; multitarget tracking problem; pattern matching problem; Application software; Computer science; Costs; Information processing; Lungs; Machine learning; Mathematics; Sensor arrays; Surveillance; Target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
  • Print_ISBN
    0-7803-8403-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2004.1381985
  • Filename
    1381985