@article {13162,
	title = {Detection and analysis of hair},
	journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
	volume = {28},
	year = {2006},
	month = {2006/07//},
	pages = {1164 - 1169},
	abstract = {We develop computational models for measuring hair appearance for comparing different people. The models and methods developed have applications to person recognition and image indexing. An automatic hair detection algorithm is described and results reported. A multidimensional representation of hair appearance is presented and computational algorithms are described. Results on a data set of 524 subjects are reported. Identification of people using hair attributes is compared to eigenface-based recognition along with a joint, eigenface-hair-based identification},
	keywords = {analysis;hair, appearance;image, AUTOMATIC, detection;, detection;hair, extraction;image, hair, indexing;multidimensional, recognition;face, recognition;feature, representation;object, representation;person},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2006.139},
	author = {Yacoob,Yaser and Davis, Larry S.}
}
@conference {12610,
	title = {Recognition of Multi-Object Events Using Attribute Grammars},
	booktitle = {Image Processing, 2006 IEEE International Conference on},
	year = {2006},
	month = {2006/10//},
	pages = {2897 - 2900},
	abstract = {We present a method for representing and recognizing visual events using attribute grammars. In contrast to conventional grammars, attribute grammars are capable of describing features that are not easily represented by finite symbols. Our approach handles multiple concurrent events involving multiple entities by associating unique object identification labels with multiple event threads. Probabilistic parsing and probabilistic conditions on the attributes are used to achieve a robust recognition system. We demonstrate the effectiveness of our method for the task of recognizing vehicle casing in parking lots and events occurring in an airport tarmac},
	keywords = {attribute, event, grammar;multiobject, grammars;image, identification, label;probabilistic, parsing;attribute, recognition;object, recognition;probability;, representation;object},
	doi = {10.1109/ICIP.2006.313035},
	author = {Joo,Seong-Wook and Chellapa, Rama}
}
@conference {12649,
	title = {Appearance modeling under geometric context},
	booktitle = {Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on},
	volume = {2},
	year = {2005},
	month = {2005/10//},
	pages = {1252 -1259 Vol. 2 - 1252 -1259 Vol. 2},
	abstract = {We propose a unified framework based on a general definition of geometric transform (GeT) for modeling appearance. GeT represents the appearance by applying designed functionals over certain geometric sets. We show that image warping, Radon transform, trace transform, etc. are special cases of our definition. Moreover, three different types of GeTs are designed to handle deformation, articulation and occlusion and applied to fingerprinting the appearance inside a contour. They include the contour-driven GeT, the feature curve based GeT and selecting functionals to model the appearance inside the convex hull of the contour. A multi-resolution representation that combines both shape and appearance information is also proposed. We apply our approach to image synthesis and object recognition. The proposed approach produces promising results when applied to fingerprinting the appearance of human and body parts despite the challenges due to articulated motion and deformations},
	keywords = {based, curve, geometry;image, GeT;convex, GeT;fingerprinting;geometric, hull;feature, information;trace, modeling;contour-driven, Radon, recognition;, recognition;shape, representation;object, synthesis;image, transform;appearance, transform;image, transform;Radon, transforms;computational, warping;multi-resolution},
	doi = {10.1109/ICCV.2005.38},
	author = {Li,Jian and Zhou,S. K and Chellapa, Rama}
}
