@conference {13071,
	title = {Action recognition using Partial Least Squares and Support Vector Machines},
	booktitle = {Image Processing (ICIP), 2011 18th IEEE International Conference on},
	year = {2011},
	month = {2011/09//},
	pages = {533 - 536},
	abstract = {We introduce an action recognition approach based on Partial Least Squares (PLS) and Support Vector Machines (SVM). We extract very high dimensional feature vectors representing spatio-temporal properties of actions and use multiple PLS regressors to find relevant features that distinguish amongst action classes. Finally, we use a multi-class SVM to learn and classify those relevant features. We applied our approach to INRIA{\textquoteright}s IXMAS dataset. Experimental results show that our method is superior to other methods applied to the IXMAS dataset.},
	keywords = {analysis;support, approach;multiclass, approximations;regression, dataset;action, dimensional, extraction;feature, extraction;image, feature, high, INRIA, IXMAS, least, machines;, machines;very, partial, properties;support, recognition, recognition;least, regressors;spatiotemporal, squares, SVM;multiple, vector, vectors},
	doi = {10.1109/ICIP.2011.6116399},
	author = {Ramadan,S. and Davis, Larry S.}
}
@conference {12687,
	title = {Robust ego-motion estimation and 3D model refinement using depth based parallax model},
	booktitle = {Image Processing, 2004. ICIP {\textquoteright}04. 2004 International Conference on},
	volume = {4},
	year = {2004},
	month = {2004/10//},
	pages = {2483 - 2486 Vol. 4 - 2483 - 2486 Vol. 4},
	abstract = {We present an iterative algorithm for robustly estimating the ego-motion and refining and updating a coarse, noisy and partial depth map using a depth based parallax model and brightness derivatives extracted from an image pair. Given a coarse, noisy and partial depth map acquired by a range-finder or obtained from a Digital Elevation Map (DFM), we first estimate the ego-motion by combining a global ego-motion constraint and a local brightness constancy constraint. Using the estimated camera motion and the available depth map estimate, motion of the 3D points is compensated. We utilize the fact that the resulting surface parallax field is an epipolar field and knowing its direction from the previous motion estimates, estimate its magnitude and use it to refine the depth map estimate. Instead of assuming a smooth parallax field or locally smooth depth models, we locally model the parallax magnitude using the depth map, formulate the problem as a generalized eigen-value analysis and obtain better results. In addition, confidence measures for depth estimates are provided which can be used to remove regions with potentially incorrect (and outliers in) depth estimates for robustly estimating ego-motion in the next iteration. Results on both synthetic and real examples are presented.},
	keywords = {3D, algorithm;, analysis;, and, based, camera;, coarse, compensation;, DEM;, depth, digital, ego-motion, eigen-value, eigenfunctions;, eigenvalues, ELEVATION, epipolar, estimation;, extraction;, feature, field;, iteration, iterative, map;, method;, methods;, model, model;, MOTION, parallax, partial, range-finding;, refinement;, refining;, surface},
	doi = {10.1109/ICIP.2004.1421606},
	author = {Agrawala, Ashok K. and Chellapa, Rama}
}
@conference {13248,
	title = {Probabilistic tracking in joint feature-spatial spaces},
	booktitle = {Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on},
	volume = {1},
	year = {2003},
	month = {2003/06//},
	pages = {I-781 - I-788 vol.1 - I-781 - I-788 vol.1},
	abstract = {In this paper, we present a probabilistic framework for tracking regions based on their appearance. We exploit the feature-spatial distribution of a region representing an object as a probabilistic constraint to track that region over time. The tracking is achieved by maximizing a similarity-based objective function over transformation space given a nonparametric representation of the joint feature-spatial distribution. Such a representation imposes a probabilistic constraint on the region feature distribution coupled with the region structure, which yields an appearance tracker that is robust to small local deformations and partial occlusion. We present the approach for the general form of joint feature-spatial distributions and apply it to tracking with different types of image features including row intensity, color and image gradient.},
	keywords = {analysis;, appearance, appearance;, color;, colour, Computer, constraint;, deformation;, detection;, distribution;, edge, estimation;, extraction;, feature, feature-spatial, feature;, function, gradient;, image, intensity;, joint, likelihood, local, maximization;, maximum, nonparametric, object, objective, occlusion;, optical, partial, probabilistic, probability;, region, representation;, row, similarity-based, small, space;, structure;, target, tracker;, tracking;, transformation, vision;},
	doi = {10.1109/CVPR.2003.1211432},
	author = {Elgammal,A. and Duraiswami, Ramani and Davis, Larry S.}
}
@article {15399,
	title = {Perturbation technique for LLG dynamics in uniformly magnetized bodies subject to RF fields},
	journal = {Magnetics, IEEE Transactions on},
	volume = {38},
	year = {2002},
	month = {2002/09//},
	pages = {2403 - 2405},
	abstract = {The problem of magnetization dynamics of a uniformly magnetized uniaxial particle or film, under elliptically polarized applied field, is considered. In the special case of circularly polarized applied field and particles (films) with a symmetry axis, pure time-harmonic magnetization modes exist that can be computed analytically. Deviations from these highly symmetric conditions are treated as perturbation of the symmetric case. The perturbation technique leads to the exactly solvable system of linear differential equations for the perturbations which enables one to compute higher order magnetization harmonic. The analytical solutions are obtained and then compared with numerical results.},
	keywords = {analytical, anisotropy, anisotropy;, applied, bodies;, circularly, component;, constant-in-time, constant;, damping, demagnetisation;, demagnetizing, differential, dynamics;, effective, elliptically, equation;, equations;, exactly, factors;, field;, film;, films;, Frequency, gyromagnetic, harmonic;, higher, Landau-Lifshitz-Gilbert, large, linear, magnetic, magnetisation;, magnetization, magnetization;, magnetized, modes;, MOTION, order, partial, particle;, particles;, perturbation, polarized, radio, ratio;, RF, saturation, solution;, solvable, system;, technique;, techniques;, thin, time-harmonic, uniaxial, uniformly},
	isbn = {0018-9464},
	doi = {10.1109/TMAG.2002.803596},
	author = {Bertotti,G. and Mayergoyz, Issak D and Serpico,C.}
}
