@conference {12665,
	title = {Moving Object Segmentation and Dynamic Scene Reconstruction Using Two Frames},
	booktitle = {Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP {\textquoteright}05). IEEE International Conference on},
	volume = {2},
	year = {2005},
	month = {2005//18/23},
	pages = {705 - 708},
	keywords = {3D, analysis;, constraints;, dynamic, ego-motion, estimation;, flow, image, images;, independent, INTENSITY, least, mean, median, method;, methods;, model;, MOTION, motion;, moving, object, of, parallax, parallax;, parametric, processing;, reconstruction;, scene, segmentation;, signal, squares, squares;, static, structure;, subspace, surface, translational, two-frame, unconstrained, video},
	doi = {10.1109/ICASSP.2005.1415502},
	author = {Agrawala, Ashok K. and Chellapa, Rama}
}
@conference {13625,
	title = {Product approximation by minimizing the upper bound of Bayes error rate for Bayesian combination of classifiers},
	booktitle = {Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on},
	volume = {1},
	year = {2004},
	month = {2004/08//},
	pages = {252 - 255 Vol.1 - 252 - 255 Vol.1},
	abstract = {In combining multiple classifiers using a Bayesian formalism, a high dimensional probability distribution is composed of a class and decisions of classifiers. In order to do product approximation of the probability distribution, the upper bound of Bayes error rate, bounded by the conditional entropy of a class and decisions, should be minimized. A second-order dependency-based product approximation is proposed in this paper by considering the second-order dependency between the class and decisions. The proposed method is evaluated by combining the classifiers recognizing unconstrained handwritten numerals.},
	keywords = {approximation;, Bayes, Bayesian, bound, character, classification;, classifiers;, conditional, distribution;, entropy;, error, formalism;, handwritten, methods;, minimisation;, multiple, numerals;, pattern, probability, probability;, Product, rate;, recognition;, statistics;, unconstrained, upper},
	doi = {10.1109/ICPR.2004.1334071},
	author = {Kang,Hee-Joong and David Doermann}
}
