• DocumentCode
    1671062
  • Title

    Sensitivity of image-based and texture-based multi-view coding to model accuracy

  • Author

    Magnor, Marcus ; Girod, Bernd

  • Author_Institution
    Inf. Syst. Lab., Stanford Univ., CA, USA
  • Volume
    3
  • fYear
    2001
  • fDate
    6/23/1905 12:00:00 AM
  • Firstpage
    98
  • Abstract
    Multi-view image coding benefits from knowledge of the depicted scene´s 3D geometry. To exploit geometry information for compression, two different approaches can be distinguished. In texture-based coding, images are converted to texture maps prior to compression. In image-based predictive coding, geometry is used for disparity compensation and occlusion detection between images. Coding performance of both approaches depends on the accuracy of the available geometry model. Texture-based and image-based coding are compared with regard to the influence of geometry accuracy on coding efficiency. The results are theoretically explained. Experiments with natural as well as synthetic image sets show that texture-based coding is more sensitive to small geometry inaccuracies than image-based coding. For approximate geometry models, image-based coding performs best, while texture-based coding yields superior coding results if scene geometry is exactly known
  • Keywords
    computational geometry; data compression; image coding; image texture; prediction theory; 3D geometry; coding efficiency; disparity compensation; geometry accuracy; image compression; image-based predictive coding; model accuracy; multi-view image coding; occlusion detection; performance; texture maps; texture-based coding; Decoding; Image coding; Information geometry; Laboratories; Layout; Pixel; Predictive coding; Predictive models; Rendering (computer graphics); Solid modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2001. Proceedings. 2001 International Conference on
  • Conference_Location
    Thessaloniki
  • Print_ISBN
    0-7803-6725-1
  • Type

    conf

  • DOI
    10.1109/ICIP.2001.958060
  • Filename
    958060