• DocumentCode
    2557161
  • Title

    A uniform Bayesian framework for integration

  • Author

    Pankanti, Sharath ; Jain, Anil K.

  • Author_Institution
    Dept. of Comput. Sci., Michigan State Univ., East Lansing, MI, USA
  • fYear
    1995
  • fDate
    21-23 Nov 1995
  • Firstpage
    497
  • Lastpage
    502
  • Abstract
    Vision researchers have advocated the integration of vision modules. However, generic system integration issues for recovering 3D information have not been adequately addressed in the literature. The authors propose a unified Bayesian integration framework for interactions among the vision modules to obtain a complete 3D reconstruction from a pair of intensity (stereo) images. The authors have integrated perceptual grouping, stereo, shape from shading, and shape from texture modules under the proposed framework. They have demonstrated that the integrated system recovers the depth and surface orientation information more reliably than the individual modules for different synthetic and real images
  • Keywords
    Bayes methods; image reconstruction; image texture; probability; stereo image processing; 3D information recovery; complete 3D reconstruction; intensity images; perceptual grouping; real images; shape from shading; shape from texture; stereo images; synthetic images; uniform Bayesian framework; vision modules; Bayesian methods; Computer science; Computer vision; Image reconstruction; Layout; Modular construction; Reflectivity; Shape; Stereo vision; Surface reconstruction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision, 1995. Proceedings., International Symposium on
  • Conference_Location
    Coral Gables, FL
  • Print_ISBN
    0-8186-7190-4
  • Type

    conf

  • DOI
    10.1109/ISCV.1995.477050
  • Filename
    477050