• DocumentCode
    1458560
  • Title

    The Geometry of Reflectance Symmetries

  • Author

    Tan, Ping ; Quan, Long ; Zickler, Todd

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore
  • Volume
    33
  • Issue
    12
  • fYear
    2011
  • Firstpage
    2506
  • Lastpage
    2520
  • Abstract
    Different materials reflect light in different ways, and this reflectance interacts with shape, lighting, and viewpoint to determine an object´s image. Common materials exhibit diverse reflectance effects, and this is a significant source of difficulty for image analysis. One strategy for dealing with this diversity is to build computational tools that exploit reflectance symmetries, such as reciprocity and isotropy, that are exhibited by broad classes of materials. By building tools that exploit these symmetries, one can create vision systems that are more likely to succeed in real-world, non-Lambertian environments. In this paper, we develop a framework for representing and exploiting reflectance symmetries. We analyze the conditions for distinct surface points to have local view and lighting conditions that are equivalent under these symmetries, and we represent these conditions in terms of the geometric structure they induce on the Gaussian sphere and its abstraction, the projective plane. We also study the behavior of these structures under perturbations of surface shape and explore applications to both calibrated and uncalibrated photometric stereo.
  • Keywords
    Gaussian processes; computational geometry; stereo image processing; Gaussian sphere; image analysis; nonLambertian environments; reflectance symmetries; reflectance symmetries geometry; stereo image processing; uncalibrated photometric stereo; Artificial neural networks; Calibration; Lighting; Photometry; Reflectivity; Surface reconstruction; Reflectance symmetry; autocalibration; photometric stereo.; projective geometry;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2011.35
  • Filename
    5719619