• DocumentCode
    3514800
  • Title

    Background recovery from video sequences using motion parameters

  • Author

    Varadarajan, Srenivas ; Karam, Lina J. ; Florencio, Dinei

  • Author_Institution
    Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ
  • fYear
    2009
  • fDate
    19-24 April 2009
  • Firstpage
    989
  • Lastpage
    992
  • Abstract
    This paper presents a novel scheme for extracting a still background occluded by a number of foreground objects, moving in different directions and velocities in a video sequence, such that every background pixel is exposed in at least one of the frames. Each identified foreground object is decomposed into blocks. The proposed scheme is able to efficiently estimate, for each foreground block, a source frame from which the occluded background pixels can be extracted. The pixels of the identified source frames are used to populate the co-located occluded pixels in the initial frame. The efficacy and the simplicity of the algorithm lie in its capacity to recover the background directly from the estimated source frames instead of performing a foreground-background classification for every frame. The proposed algorithm is robust to variations in lighting and is effective in removing both rigid and deformable foreground objects. Simulation results are presented to illustrate the performance of the proposed scheme.
  • Keywords
    image classification; image motion analysis; image resolution; image sequences; background pixel; foreground objects; foreground-background classification; motion parameters; occlusion removal; video sequences; Clustering algorithms; Content based retrieval; Data mining; Heart; Pixel; Robustness; Surveillance; Tracking; Video coding; Video sequences; Background Extraction; Motion; Object Removal; Occlusion Removal; Video;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
  • Conference_Location
    Taipei
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4244-2353-8
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2009.4959752
  • Filename
    4959752