• DocumentCode
    952810
  • Title

    Multiview Stereo via Volumetric Graph-Cuts and Occlusion Robust Photo-Consistency

  • Author

    Vogiatzis, George ; Hernandez, C. ; Torr, Philip H S ; Cipolla, Roberto

  • Author_Institution
    Toshiba Res. Eur. Ltd., Cambridge
  • Volume
    29
  • Issue
    12
  • fYear
    2007
  • Firstpage
    2241
  • Lastpage
    2246
  • Abstract
    This paper presents a volumetric formulation for the multiview stereo problem which is amenable to a computationally tractable global optimization using Graph-cuts. Our approach is to seek the optimal partitioning of 3D space into two regions labeled as "object" and "empty" under a cost functional consisting of the following two terms: 1) A term that forces the boundary between the two regions to pass through photo-consistent locations; and 2) a ballooning term that inflates the "object" region. To take account of the effect of occlusion on the first term, we use an occlusion robust photo-consistency metric based on normalized cross correlation, which does not assume any geometric knowledge about the reconstructed object. The globally optimal 3D partitioning can be obtained as the minimum cut solution of a weighted graph.
  • Keywords
    computational geometry; flow graphs; image reconstruction; object detection; optimisation; solid modelling; stereo image processing; 3D object image reconstruction; discrete flow graph; global optimization; multiview stereo problem; normalized cross correlation; object region; occlusion robust photo-consistency; volumetric graph-cuts; weighted graph; Algorithms; Artificial Intelligence; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Pattern Recognition, Automated; Photogrammetry; Reproducibility of Results; Sensitivity and Specificity;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2007.70712
  • Filename
    4359958