@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}
}
@conference {12761,
	title = {Quasi-invariants for human action representation and recognition},
	booktitle = {Pattern Recognition, 2002. Proceedings. 16th International Conference on},
	volume = {1},
	year = {2002},
	month = {2002///},
	pages = {307 - 310 vol.1 - 307 - 310 vol.1},
	abstract = {Although human action recognition has been the subject of much research in the past, the issue of viewpoint invariance has received scarce attention. In this paper, we present an approach to detect human action with a high tolerance to viewpoint change. Canonical body poses are modeled in a view invariant manner to enable detection from a general viewpoint. While there exist no invariants for 3D to 2D projection, there exists a wealth of techniques in 2D invariance that can be used to advantage in 3D to 2D projection. We employ 2D invariants to recognize canonical poses of the human body leading to an effective way to represent and recognize human action which we evaluate theoretically and experimentally on 2D projections of publicly available human motion capture data.},
	keywords = {2D, action, analysis;, body, canonical, change, human, image, invariance;, MOTION, poses;, quasi-invariants;, recognition;, representation;, tolerance;, viewpoint},
	doi = {10.1109/ICPR.2002.1044699},
	author = {Parameswaran, V. and Chellapa, Rama}
}
