• DocumentCode
    1283256
  • Title

    Integrate tool for online analysis and offline mining of people trajectories

  • Author

    Calderara, Simone ; Prati, Andrea ; Cucchiara, Rita

  • Author_Institution
    Dipt. di Ing. dell´Inf., Univ. of Modena & Reggio Emilia, Modena, Italy
  • Volume
    6
  • Issue
    4
  • fYear
    2012
  • fDate
    7/1/2012 12:00:00 AM
  • Firstpage
    334
  • Lastpage
    347
  • Abstract
    In the past literature, online alarm-based video-surveillance and offline forensic-based data mining systems are often treated separately, even from different scientific communities. However, the founding techniques are almost the same and, despite some examples in commercial systems, the cases on which an integrated approach is followed are limited. For this reason, this study describes an integrated tool capable of putting together these two subsystems in an effective way. Despite its generality, the proposal is here reported in the case of people trajectory analysis, both in real time and offline. Trajectories are modelled based on either their spatial location or their shape, and proper similarity measures are proposed. Special solutions to meet real-time requirements in both cases are also presented and the trade-off between efficiency and efficacy is analysed by comparing when using a statistical model and when not. Examples of results in large datasets acquired in the University campus are reported as preliminary evaluation of the system.
  • Keywords
    computer forensics; data mining; statistical analysis; video surveillance; commercial systems; founding techniques; integrate tool; integrated tool; large datasets; offline forensic-based data mining systems; offline mining; online alarm-based video-surveillance; online analysis; people trajectory analysis; preliminary system evaluation; real-time requirements; scientific community; similarity measures; spatial location; statistical model; university campus;
  • fLanguage
    English
  • Journal_Title
    Computer Vision, IET
  • Publisher
    iet
  • ISSN
    1751-9632
  • Type

    jour

  • DOI
    10.1049/iet-cvi.2010.0143
  • Filename
    6298762