• DocumentCode
    1025440
  • Title

    Image-based rendering of range data with estimated depth uncertainty

  • Author

    Hofsetz, Christian ; Ng, Kim ; Chen, George ; McGuinness, Peter ; Max, Nelson ; Liu, Yang

  • Author_Institution
    Dept. of Comput. Sci., Univ. do Vale do Rio dos Sinos, Brazil
  • Volume
    24
  • Issue
    4
  • fYear
    2004
  • Firstpage
    34
  • Lastpage
    41
  • Abstract
    Image-based rendering (IBR) involves constructing an image from a new viewpoint, using several input images from different viewpoints. Our approach is to acquire or estimate the depth for each pixel of each input image. We then reconstruct the new view from the resulting collection of 3D points. When rendering images from photographs, acquiring and registering data is far from perfect. Accuracy can fluctuate, depending on the choice of geometry reconstruction technique. Our image-rendering approach involves three steps: depth extraction, uncertainty estimation, and rendering. That is, we first compute a depth map for every input image. Then we calculate the uncertainty information using the estimated depth maps as starting points. Finally, we perform the actual rendering, which renders the uncertainty estimated in the previous step as ellipsoidal Gaussian splats.
  • Keywords
    computational geometry; computer vision; data visualisation; feature extraction; image reconstruction; rendering (computer graphics); uncertainty handling; computer vision; data acquisition; data registration; depth extraction; ellipsoidal Gaussian splats; estimated depth uncertainty; geometry reconstruction technique; image-based rendering; range data; uncertainty estimation; Cameras; Filling; Image reconstruction; Information geometry; Kernel; Laboratories; Layout; Pixel; Rendering (computer graphics); Uncertainty; Algorithms; Artificial Intelligence; Cluster Analysis; Computer Graphics; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Photogrammetry; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique; User-Computer Interface;
  • fLanguage
    English
  • Journal_Title
    Computer Graphics and Applications, IEEE
  • Publisher
    ieee
  • ISSN
    0272-1716
  • Type

    jour

  • DOI
    10.1109/MCG.2004.8
  • Filename
    1310209