@conference {12701,
	title = {Illuminating light field: image-based face recognition across illuminations and poses},
	booktitle = {Automatic Face and Gesture Recognition, 2004. Proceedings. Sixth IEEE International Conference on},
	year = {2004},
	month = {2004/05//},
	pages = {229 - 234},
	abstract = {We present an image-based method for face recognition across different illuminations and different poses, where the term {\textquoteright}image-based{\textquoteright} means that only 2D images are used and no explicit 3D models are needed. As face recognition across illuminations and poses involves three factors, namely identity, illumination, and pose, generalizations from known identities to novel identities, from known illuminations to novel illuminations, and from known poses to unknown poses are desired. Our approach, called the illuminating light field, derives an identity signature that is invariant to illuminations and poses, where a subspace encoding is assumed for the identity, a Lambertain reflectance model for the illumination, and a light field model for the poses. Experimental results using the PIE database demonstrate the effectiveness of the proposed approach.},
	keywords = {Face, field;, illuminating, image-based, Lambertain, light, lighting;, model;, multidimensional, poses;, processing;, recognition;, reflectance, reflectivity;, signal},
	doi = {10.1109/AFGR.2004.1301536},
	author = {Zhou,Shaohua and Chellapa, Rama}
}
@article {14886,
	title = {Lambertian reflectance and linear subspaces},
	journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
	volume = {25},
	year = {2003},
	month = {2003/02//},
	pages = {218 - 233},
	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 recognition based on linear methods as well as algorithms that use convex optimization to enforce nonnegative lighting functions. We also show a simple way to enforce nonnegative lighting when the images of an object lie near a 4D linear space. We apply these algorithms to perform face recognition by finding the 3D model that best matches a 2D query image.},
	keywords = {2D, 4D, 9D, analog;, analytic, characterization;, convex, convolution, distant, functions;, harmonics;, image, image;, intensities;, Lambertian, light, lighting, linear, methods;, nonnegative, normals;, object, optimization;, programming;, query, recognition;, reflectance;, reflectivity;, set;, sources;, space;, spherical, subspace;, subspaces;, surface},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2003.1177153},
	author = {Basri,R. and Jacobs, David W.}
}
@article {14988,
	title = {Models and high-performance algorithms for global BRDF retrieval},
	journal = {Computational Science Engineering, IEEE},
	volume = {5},
	year = {1998},
	month = {1998/12//oct},
	pages = {16 - 29},
	abstract = {The authors describe three models for retrieving information related to the scattering of light on the Earth{\textquoteright}s surface. Using these models, they{\textquoteright}ve developed algorithms for the IBM SP2 that efficiently retrieve this information},
	keywords = {algorithms;, BRDF, Earth, geomorphology;, geophysical, global, high-performance, IBM, information, light, machines;, models;, Parallel, processing;, reflectivity;, retrieval, retrieval;, scattering;, signal, SP2;, surface;},
	isbn = {1070-9924},
	doi = {10.1109/99.735892},
	author = {Zengyan Zhang and Kalluri, SNV and JaJa, Joseph F. and Liang,Shunlin and Townshend,J.R.G.}
}
