• DocumentCode
    3674355
  • Title

    Online pedestrian group walking event detection using spectral analysis of motion similarity graph

  • Author

    Vahid Bastani;Damian Campo;Lucio Marcenaro;Carlo Regazzoni

  • Author_Institution
    University of Genoa, DITEN, Via all´Opera Pia, 11A - 16145 Genova (GE), Italy
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    A method for online identification of group of moving objects in the video is proposed in this paper. This method at each frame identifies group of tracked objects with similar local instantaneous motion pattern using spectral clustering on motion similarity graph. Then, the output of the algorithm is used to detect the event of more than two object moving together as required by PETS2015 challenge. The performance of the algorithm is evaluated on the PETS2015 dataset.
  • Keywords
    "Clustering algorithms","Legged locomotion","Kalman filters","Cameras","Trajectory","Eigenvalues and eigenfunctions","Hidden Markov models"
  • Publisher
    ieee
  • Conference_Titel
    Advanced Video and Signal Based Surveillance (AVSS), 2015 12th IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/AVSS.2015.7301744
  • Filename
    7301744
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3674355