• DocumentCode
    3333710
  • Title

    What Object Motion Reveals about Shape with Unknown BRDF and Lighting

  • Author

    Chandraker, Manmohan ; Reddy, Deepti ; Yizhou Wang ; Ramamoorthi, Ravi

  • fYear
    2013
  • fDate
    23-28 June 2013
  • Firstpage
    2523
  • Lastpage
    2530
  • Abstract
    We present a theory that addresses the problem of determining shape from the (small or differential) motion of an object with unknown isotropic reflectance, under arbitrary unknown distant illumination, for both orthographic and perpsective projection. Our theory imposes fundamental limits on the hardness of surface reconstruction, independent of the method involved. Under orthographic projection, we prove that three differential motions suffice to yield an invariant that relates shape to image derivatives, regardless of BRDF and illumination. Under perspective projection, we show that four differential motions suffice to yield depth and a linear constraint on the surface gradient, with unknown BRDF and lighting. Further, we delineate the topological classes up to which reconstruction may be achieved using the invariants. Finally, we derive a general stratification that relates hardness of shape recovery to scene complexity. Qualitatively, our invariants are homogeneous partial differential equations for simple lighting and inhomogeneous for complex illumination. Quantitatively, our framework shows that the minimal number of motions required to resolve shape is greater for more complex scenes. Prior works that assume brightness constancy, Lambertian BRDF or a known directional light source follow as special cases of our stratification. We illustrate with synthetic and real data how potential reconstruction methods may exploit our framework.
  • Keywords
    brightness; image motion analysis; image reconstruction; lighting; natural scenes; partial differential equations; arbitrary unknown distant illumination; brightness constancy; complex illumination; differential motions; homogeneous partial differential equations; lighting; linear constraint; object motion; orthographic projection; perpsective projection; real data; reconstruction methods; scene complexity; shape recovery; stratification; surface gradient; surface reconstruction; synthetic data; topological classes; unknown BRDF; unknown isotropic reflectance; yield depth; Brightness; Cameras; Image reconstruction; Lighting; Optical imaging; Shape; Surface reconstruction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on
  • Conference_Location
    Portland, OR
  • ISSN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2013.326
  • Filename
    6619170