• DocumentCode
    539175
  • Title

    Airborne monitoring of ground traffic behaviour for hidden threat assessment

  • Author

    Seungkeun Kim ; Zbikowski, R.W. ; Tsourdos, A. ; White, B.A.

  • Author_Institution
    Dept. of Inf. & Sensors, Cranfield Univ., Swindon, UK
  • fYear
    2010
  • fDate
    26-29 July 2010
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    This paper focuses on development of behaviour recognition technique for airborne monitoring of ground traffic to detect hidden threats. To enhance tracking accuracy, sensor fusion and smoothing are applied with Kalman filter. To tackle behaviour recognition, trajectory approximation and classification methodology is proposed using differential geometric quantities and string matching. Simulation on a ground vehicle is done to verify the feasibility of the proposed algorithms.
  • Keywords
    Kalman filters; computerised monitoring; image classification; sensor fusion; traffic engineering computing; Kalman filter; airborne monitoring; behaviour recognition technique; ground traffic behaviour; hidden threat assessment; sensor fusion; string matching; trajectory approximation; Acceleration; Approximation methods; History; Sensor fusion; Trajectory; Vehicles; Sensor fusion; behaviour recognition; string matching; tracking filter; trajectory classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Fusion (FUSION), 2010 13th Conference on
  • Conference_Location
    Edinburgh
  • Print_ISBN
    978-0-9824438-1-1
  • Type

    conf

  • DOI
    10.1109/ICIF.2010.5711999
  • Filename
    5711999