Lambertian reflectance and linear subspaces

Weizmann Institute of Science · Princeton University

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Abstract

We prove that the set of all Lambertian reflectance functions (the mapping from surface normals to intensities) obtained with arbitrary distant light sources lies close to a 9D linear subspace. This implies that, in general, the set of images of a convex Lambertian object obtained under a wide variety of lighting conditions can be approximated accurately by a low-dimensional linear subspace, explaining prior empirical results. We also provide a simple analytic characterization of this linear space. We obtain these results by representing lighting using spherical harmonics and describing the effects of Lambertian materials as the analog of a convolution. These results allow us to construct algorithms for object…

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1,582
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43.92
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100%
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Authors

2

Topics & keywords

Keywords
  • Linear subspace
  • Subspace topology
  • Artificial intelligence
  • Convolution (computer science)
  • Computer vision
  • Mathematics
  • Computer science
  • Set (abstract data type)
UN Sustainable Development Goals
  • Sustainable cities and communities
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