• DocumentCode
    127442
  • Title

    A networked high-speed vision system for vehicle tracking

  • Author

    Noda, Akihito ; Hirano, Masahiro ; Yamakawa, Yuji ; Ishikawa, Masatoshi

  • Author_Institution
    Grad. Sch. of Frontier Sci., Univ. of Tokyo, Kashiwa, Japan
  • fYear
    2014
  • fDate
    18-20 Feb. 2014
  • Firstpage
    343
  • Lastpage
    348
  • Abstract
    This paper presents a networked vision system for tracking high-speed objects moving across multiple cameras´ fields of view. Tracking vehicles that travel along highway is one of the potential applications, and the vehicles can be continuously tracked from the entrance to the exit without being lost. Such a system can be used for surveillance and analysis of traffic congestions/accidents. Each vehicle passes a large number of cameras at high speed, one ofter another. Higher frame rate and faster data communication are desired for reliable target tracking and system scalability. We developed a prototype system that captures the moving vehicle with 1000 frames-per-second and that shares the small feature data only between a pair of adjacent cameras. A 1/10-scale vehicle moving across two cameras at 2500 mm/s ≈ 9 km/h was successfully tracked by the experimental system. Tracking a laser pointer spot moving at faster than 100 km/h on the floor is also demonstrated.
  • Keywords
    cameras; computer vision; data communication; feature extraction; object tracking; surveillance; traffic engineering computing; camera fields of view; data communication; high-speed object tracking; laser pointer spot tracking; networked high-speed vision system; system scalability; target tracking; traffic accident analysis; traffic accident surveillance; traffic congestion analysis; traffic congestion surveillance; vehicle tracking; Delays; Lasers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Sensors Applications Symposium (SAS), 2014 IEEE
  • Conference_Location
    Queenstown
  • Print_ISBN
    978-1-4799-2180-5
  • Type

    conf

  • DOI
    10.1109/SAS.2014.6798973
  • Filename
    6798973