• DocumentCode
    2501266
  • Title

    Dynamics Based Trajectory Segmentation for UAV videos

  • Author

    Banerjee, Prithviraj ; Nevatia, Ram

  • Author_Institution
    Inst. for Robot. & Intell. Syst., Univ. of Southern California, Los Angeles, CA, USA
  • fYear
    2010
  • fDate
    Aug. 29 2010-Sept. 1 2010
  • Firstpage
    345
  • Lastpage
    352
  • Abstract
    A novel representation of vehicle trajectories is proposed for applications in trajectory analysis and activity detection. Specifically, a piecewise arc fitting based smoothing algorithm is proposed for denoising the trajectories. A dynamic program is used to find the optimal arc fit to a given trajectory. We motivate the usage of dynamic primitives to parametrize common vehicular activities, and propose a dynamics based trajectory segmentation algorithm. Each primitive is modeled using a second order Auto-Regressive model, and form useful descriptors for a given vehicular trajectory. We evaluate both our trajectory smoothing and dynamic trajectory segmentation algorithm on a real UAV video dataset, and show performance improvements which clearly motivate its wide applicability in a general trajectory analysis system.
  • Keywords
    aircraft; autoregressive processes; curve fitting; image denoising; image segmentation; mobile robots; object detection; remotely operated vehicles; smoothing methods; traffic engineering computing; video signal processing; UAV video; activity detection; dynamics based trajectory segmentation; fitting based smoothing algorithm; optimal arc fit; second order autoregressive model; trajectory analysis; trajectory denoising; unmanned aerial vehicle; Approximation algorithms; Computational modeling; Heuristic algorithms; Mathematical model; Smoothing methods; Trajectory; Vehicle dynamics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Video and Signal Based Surveillance (AVSS), 2010 Seventh IEEE International Conference on
  • Conference_Location
    Boston, MA
  • Print_ISBN
    978-1-4244-8310-5
  • Type

    conf

  • DOI
    10.1109/AVSS.2010.23
  • Filename
    5597102