• DocumentCode
    2948637
  • Title

    Compressive sensing in video applications

  • Author

    Orovic, Irena ; Park, Soojin ; Stankovic, Stevan

  • Author_Institution
    Fac. of Electr. Eng., Univ. of Montenegro, Podgorica, Montenegro
  • fYear
    2013
  • fDate
    26-28 Nov. 2013
  • Firstpage
    745
  • Lastpage
    748
  • Abstract
    In this paper, a new approach to estimate motion parameters in compressive sensed video sequences is proposed. The proposed procedure combines sparse reconstruction algorithms and time-frequency analysis applied to μ-propagation signal. This concept allows providing precise velocity estimation even under a reduced number of randomly chosen video frames. The theory is applied and illustrated on synthetic and real video sequence.
  • Keywords
    compressed sensing; image reconstruction; image sequences; motion estimation; time-frequency analysis; video signal processing; μ-propagation signal; compressive sensed video sequences; motion parameter estimation; sparse reconstruction algorithms; time-frequency analysis; velocity estimation; video frames; Compressed sensing; Estimation; Frequency estimation; Time-frequency analysis; Vectors; Video sequences; Compressive sensing; motion parameters estimation; random frames recording; reconstruction algorithms; velocity; video signals;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Telecommunications Forum (TELFOR), 2013 21st
  • Conference_Location
    Belgrade
  • Print_ISBN
    978-1-4799-1419-7
  • Type

    conf

  • DOI
    10.1109/TELFOR.2013.6716337
  • Filename
    6716337