@conference {14857,
	title = {Lambertian reflectance and linear subspaces},
	booktitle = {Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on},
	volume = {2},
	year = {2001},
	month = {2001///},
	pages = {383 -390 vol.2 - 383 -390 vol.2},
	abstract = {We prove that the set of all reflectance functions (the mapping from surface normals to intensities) produced by Lambertian objects under distant, isotropic lighting lies close to a 9D linear subspace. This implies that the images of a convex Lambertian object obtained under a wide variety of lighting conditions can be approximated accurately with 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 recognition based on linear methods as well as algorithms that use convex optimization to enforce non-negative lighting functions},
	keywords = {functions;spherical, harmonics;convex, Lambertian, lighting;object, object;convex, objects;convex, optimization;isotropic, programming;object, recognition;, recognition;reflectance},
	doi = {10.1109/ICCV.2001.937651},
	author = {Basri,R. and Jacobs, David W.}
}
