• DocumentCode
    2996467
  • Title

    A Multi-sensor Traffic Scene Dataset with Omnidirectional Video

  • Author

    Koschorrek, Philipp ; Piccini, Tommaso ; Oberg, Per ; Felsberg, Michael ; Nielsen, Larry ; Mester, Rudolf

  • Author_Institution
    Dept. of Electr. Eng., Linkoping Univ., Linkoping, Sweden
  • fYear
    2013
  • fDate
    23-28 June 2013
  • Firstpage
    727
  • Lastpage
    734
  • Abstract
    The development of vehicles that perceive their environment, in particular those using computer vision, indispensably requires large databases of sensor recordings obtained from real cars driven in realistic traffic situations. These datasets should be time shaped for enabling synchronization of sensor data from different sources. Furthermore, full surround environment perception requires high frame rates of synchronized omnidirectional video data to prevent information loss at any speeds. This paper describes an experimental setup and software environment for recording such synchronized multi-sensor data streams and storing them in a new open source format. The dataset consists of sequences recorded in various environments from a car equipped with an omnidirectional multi-camera, height sensors, an IMU, a velocity sensor, and a GPS. The software environment for reading these data sets will be provided to the public, together with a collection of long multi-sensor and multi-camera data streams stored in the developed format.
  • Keywords
    computer vision; public domain software; software engineering; traffic information systems; very large databases; video signal processing; GPS; IMU; computer vision; large databases; multisensor traffic scene dataset; omnidirectional video; open source format; realistic traffic situations; software environment; synchronized multisensor data streams; vehicle development; velocity sensor; Cameras; Computers; Global Positioning System; Robot sensing systems; Software; Synchronization; Visualization; automotive; benchmark; dataset; multi-sensor; omnidirectional; surround sensing; synchronized; traffic; vision;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition Workshops (CVPRW), 2013 IEEE Conference on
  • Conference_Location
    Portland, OR
  • Type

    conf

  • DOI
    10.1109/CVPRW.2013.110
  • Filename
    6595954