• DocumentCode
    144971
  • Title

    Enhanced motion cues for automatic depth extraction for 2D-to-3D video conversion

  • Author

    Alves, Gustavo O. de E. ; da Silva, E.A.B.

  • Author_Institution
    PEE/COPPE, Fed. Univ. of Rio de Janeiro, Rio de Janeiro, Brazil
  • fYear
    2014
  • fDate
    17-20 Aug. 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In this paper we present two methods of depth extraction for 2D-to-3D video conversion. One for a scene captured with a static camera and other for the case of a moving camera, both using information from the motion present on the scene. In the first method, temporal difference, morphological operations and a region filling technique are used to segment the moving objects and define the foreground. Moreover, analysis of how the detected regions vary over nearby frames is applied to ensure the temporal consistency. For the regions corresponding to background, depth values are obtained merging information from linear perspective and texture characteristics. The second method is applied when a dynamic background is detected. It requires an input sequence encoded with H.264, so the motion information extracted from the compressed bitstream is used to assign depth values for the entire scene.
  • Keywords
    image motion analysis; image segmentation; image texture; object detection; three-dimensional television; video signal processing; 2D-to-3D video conversion; automatic depth extraction; compressed bitstream; dynamic background detection; morphological operations; motion cues enhancement; moving camera; region filling technique; static camera; temporal consistency; temporal difference; texture characteristics; Cameras; Data mining; Image edge detection; Motion segmentation; Noise; Three-dimensional displays; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Telecommunications Symposium (ITS), 2014 International
  • Conference_Location
    Sao Paulo
  • Type

    conf

  • DOI
    10.1109/ITS.2014.6947992
  • Filename
    6947992