• DocumentCode
    3674352
  • Title

    PETS 2015: Datasets and challenge

  • Author

    Longzhen Li;Tahir Nawaz;James Ferryman

  • Author_Institution
    Computational Vision Group, School of Systems Engineering, University of Reading, UK
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents the two datasets (ARENA and P5) and the challenge that form a part of the PETS 2015 workshop. The datasets consist of scenarios recorded by using multiple visual and thermal sensors. The scenarios in ARENA dataset involve different staged activities around a parked vehicle in a parking lot in UK and those in P5 dataset involve different staged activities around the perimeter of a nuclear power plant in Sweden. The scenarios of each dataset are grouped into `Normal´, `Warning´ and `Alarm´ categories. The Challenge specifically includes tasks that account for different steps in a video understanding system: Low-Level Video Analysis (object detection and tracking), Mid-Level Video Analysis (`atomic´ event detection) and High-Level Video Analysis (`complex´ event detection). The evaluation methodology used for the Challenge includes well-established measures.
  • Keywords
    "Positron emission tomography","Thermal sensors","Cameras","Event detection","Visualization","Vehicles"
  • Publisher
    ieee
  • Conference_Titel
    Advanced Video and Signal Based Surveillance (AVSS), 2015 12th IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/AVSS.2015.7301741
  • Filename
    7301741