• DocumentCode
    3185633
  • Title

    Moving Vehicle Registration and Super-Resolution

  • Author

    Wheeler, Frederick W. ; Hoogs, Anthony J.

  • Author_Institution
    GE Global Res., Niskayuna
  • fYear
    2007
  • fDate
    10-12 Oct. 2007
  • Firstpage
    101
  • Lastpage
    107
  • Abstract
    We describe a method for registering and super-resolving moving vehicles from aerial surveillance video. The challenge of vehicle super-resolution lies in the fact that vehicles may be very small and thus frame-to-frame registration does not offer enough constraints to yield registration with sub-pixel accuracy. To overcome this, we first register the large-scale image backgrounds and then, relative to the background registration, register the small-scale moving vehicle over all frames simultaneously using a vehicle motion model. To solve for the vehicle motion parameters we optimize a cost function that incorporates both vehicle appearance and background appearance consistency. Once this process accurately registers a moving vehicle, it is super-resolved. We apply both a frequency domain and a spatial domain approach. The frequency domain approach can be used when the final registered vehicle motion is well approximated by shifts in the image plane. The robust regularized spatial domain approach handles all cases of vehicle motion.
  • Keywords
    approximation theory; image motion analysis; image registration; image resolution; optimisation; video surveillance; aerial surveillance video; cost function optimisation; frame-to-frame registration; image background registration; moving vehicle registration; moving vehicle super-resolution; regularized spatial domain approach; vehicle motion approximation; Cost function; Frequency domain analysis; Image resolution; Image restoration; Layout; Motion estimation; Pattern recognition; Spatial resolution; Surveillance; Vehicles; aerial surveillance; super-resolution; vehicle;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applied Imagery Pattern Recognition Workshop, 2007. AIPR 2007. 36th IEEE
  • Conference_Location
    Washington, DC
  • ISSN
    1550-5219
  • Print_ISBN
    978-0-7695-3066-6
  • Type

    conf

  • DOI
    10.1109/AIPR.2007.7
  • Filename
    4476130