@conference {12511,
	title = {Enhancing sparsity using gradients for compressive sensing},
	booktitle = {Image Processing (ICIP), 2009 16th IEEE International Conference on},
	year = {2009},
	month = {2009/11//},
	pages = {3033 - 3036},
	abstract = {In this paper, we propose a reconstruction method that recovers images assumed to have a sparse representation in a gradient domain by using partial measurement samples that are collected in the Fourier domain. A key improvement of this technique is that it makes use of a robust generalized Poisson solver that greatly aids in achieving a significantly improved performance over similar proposed methods. Experiments provided also demonstrate that this new technique is more flexible to work with either random or restricted sampling scenarios better than its competitors.},
	keywords = {analysis;gradient, domain;compressive, domain;image, Fourier, generalized, measurement, methods;, methods;image, Poisson, reconstruction;image, reconstruction;partial, representation;Fourier, representation;sampling, samples;robust, scenarios;sparse, sensing;enhancing, solver;sampling, sparsity;gradient},
	doi = {10.1109/ICIP.2009.5414411},
	author = {Patel, Vishal M. and Easley,G. R and Chellapa, Rama and Healy,D. M}
}
@conference {13978,
	title = {Canny edge detection on NVIDIA CUDA},
	booktitle = {Computer Vision and Pattern Recognition Workshops, 2008. CVPRW {\textquoteright}08. IEEE Computer Society Conference on},
	year = {2008},
	month = {2008/06//},
	pages = {1 - 8},
	abstract = {The Canny edge detector is a very popular and effective edge feature detector that is used as a pre-processing step in many computer vision algorithms. It is a multi-step detector which performs smoothing and filtering, non-maxima suppression, followed by a connected-component analysis stage to detect ldquotruerdquo edges, while suppressing ldquofalserdquo non edge filter responses. While there have been previous (partial) implementations of the Canny and other edge detectors on GPUs, they have been focussed on the old style GPGPU computing with programming using graphical application layers. Using the more programmer friendly CUDA framework, we are able to implement the entire Canny algorithm. Details are presented along with a comparison with CPU implementations. We also integrate our detector in to MATLAB, a popular interactive simulation package often used by researchers. The source code will be made available as open source.},
	keywords = {algorithms;connected-component, analysis, application, Canny, CUDA;computer, detection;feature, detection;NVIDIA, detector;filtering;graphical, detector;non, edge, extraction;smoothing, feature, filter, layers;multistep, methods;, responses;nonmaxima, stage;edge, suppression;smoothing;computer, VISION, vision;edge},
	doi = {10.1109/CVPRW.2008.4563088},
	author = {Luo,Yuancheng and Duraiswami, Ramani}
}
@conference {12650,
	title = {An algebraic approach to surface reconstruction from gradient fields},
	booktitle = {Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on},
	volume = {1},
	year = {2005},
	month = {2005/10//},
	pages = {174 - 181 Vol. 1 - 174 - 181 Vol. 1},
	abstract = {Several important problems in computer vision such as shape from shading (SFS) and photometric stereo (PS) require reconstructing a surface from an estimated gradient field, which is usually non-integrable, i.e. have non-zero curl. We propose a purely algebraic approach to enforce integrability in discrete domain. We first show that enforcing integrability can be formulated as solving a single linear system Ax =b over the image. In general, this system is under-determined. We show conditions under which the system can be solved and a method to get to those conditions based on graph theory. The proposed approach is non-iterative, has the important property of local error confinement and can be applied to several problems. Results on SFS and PS demonstrate the applicability of our method.},
	keywords = {algebra;, algebraic, approach;, Computer, confinement;, discrete, domain, error, field;, from, gradient, graph, image, integrability;, linear, local, methods;, photometric, reconstruction;, shading;, SHAPE, stereo;, surface, system;, theory;, vision;},
	doi = {10.1109/ICCV.2005.31},
	author = {Agrawal,A. and Chellapa, Rama and Raskar, R.}
}
@article {18191,
	title = {Data hiding in curves with application to fingerprinting maps},
	journal = {Signal Processing, IEEE Transactions on},
	volume = {53},
	year = {2005},
	month = {2005/10//},
	pages = {3988 - 4005},
	abstract = {This paper presents a new data hiding method for curves. The proposed algorithm parameterizes a curve using the B-spline model and adds a spread spectrum sequence to the coordinates of the B-spline control points. In order to achieve robust fingerprint detection, an iterative alignment-minimization algorithm is proposed to perform curve registration and to deal with the nonuniqueness of B-spline control points. Through experiments, we demonstrate the robustness of the proposed data-hiding algorithm against various attacks, such as collusion, cropping, geometric transformations, vector/raster-raster/vector conversions, printing-and-scanning, and some of their combinations. We also show the feasibility of our method for fingerprinting topographic maps as well as writings and drawings.},
	keywords = {(mathematics);, algorithm;, alignment-minimization, B-spline, CONTROL, curve, data, detection;, edge, embedding;, encapsulation;, fingerprint, geospatial, hiding, identification;, image, iterative, method;, methods;, minimisation;, point;, protection;, registration;, sequence;, spectrum, splines, spread, watermarking;},
	isbn = {1053-587X},
	doi = {10.1109/TSP.2005.855411},
	author = {Gou,Hongmei and M. Wu}
}
@conference {13188,
	title = {Detecting rotational symmetries},
	booktitle = {Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on},
	volume = {2},
	year = {2005},
	month = {2005/10//},
	pages = {954 - 961 Vol. 2 - 954 - 961 Vol. 2},
	abstract = {We present an algorithm for detecting multiple rotational symmetries in natural images. Given an image, its gradient magnitude field is computed, and information from the gradients is spread using a diffusion process in the form of a gradient vector flow (GVF) field. We construct a graph whose nodes correspond to pixels in tire image, connecting points that are likely to be rotated versions of one another The n-cycles present in tire graph are made to vote for C<sub>n</sub> symmetries, their votes being weighted by the errors in transformation between GVF in the neighborhood of the voting points, and the irregularity of the n-sided polygons formed by the voters. The votes are accumulated at tire centroids of possible rotational symmetries, generating a confidence map for each order of symmetry. We tested the method with several natural images.},
	keywords = {axial, computational, detection;, field;, flow;, geometry;, gradient, graph, graph;, image, image;, magnitude, methods;, multiple, n-sided, object, polygons;, recognition;, rotational, symmetries;, symmetry;, theory;, tire, tyres;, vector},
	doi = {10.1109/ICCV.2005.71},
	author = {Shiv Naga Prasad,V. and Davis, Larry S.}
}
@conference {13186,
	title = {Fast multiple object tracking via a hierarchical particle filter},
	booktitle = {Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on},
	volume = {1},
	year = {2005},
	month = {2005/10//},
	pages = {212 - 219 Vol. 1 - 212 - 219 Vol. 1},
	abstract = {A very efficient and robust visual object tracking algorithm based on the particle filter is presented. The method characterizes the tracked objects using color and edge orientation histogram features. While the use of more features and samples can improve the robustness, the computational load required by the particle filter increases. To accelerate the algorithm while retaining robustness we adopt several enhancements in the algorithm. The first is the use of integral images for efficiently computing the color features and edge orientation histograms, which allows a large amount of particles and a better description of the targets. Next, the observation likelihood based on multiple features is computed in a coarse-to-fine manner, which allows the computation to quickly focus on the more promising regions. Quasi-random sampling of the particles allows the filter to achieve a higher convergence rate. The resulting tracking algorithm maintains multiple hypotheses and offers robustness against clutter or short period occlusions. Experimental results demonstrate the efficiency and effectiveness of the algorithm for single and multiple object tracking.},
	keywords = {(numerical, algorithm;, analysis;, Color, colour, Computer, Convergence, detection;, edge, fast, filter;, Filtering, hierarchical, histogram;, image, images;, integral, likelihood;, methods);, methods;, multiple, numerical, object, observation, of, orientation, particle, processes;, quasirandom, random, sampling;, tracking, tracking;, vision;, visual},
	doi = {10.1109/ICCV.2005.95},
	author = {Yang,Changjiang and Duraiswami, Ramani and Davis, Larry S.}
}
@conference {13335,
	title = {The half-edge tree: a compact data structure for level-of-detail tetrahedral meshes},
	booktitle = {Shape Modeling and Applications, 2005 International Conference},
	year = {2005},
	month = {2005/06//},
	pages = {332 - 337},
	abstract = {We propose a new data structure for the compact encoding of a level-of detail (LOD) model of a three-dimensional scalar field based on unstructured tetrahedral meshes. Such data structure, called a half-edge tree (HET), is built through the iterative application of a half-edge collapse, i.e. by contracting an edge to one of its endpoints. We also show that selective refined meshes extracted from an HET contain on average about 34\% and up to 75\% less tetrahedra than those extracted from an LOD model built through a general edge collapse.},
	keywords = {application;, compact, computational, data, detection;, edge, encoding;, generation;, geometry;, half-edge, iterative, level-of-detail, mesh, meshes;, methods;, model;, structure;, structures;, tetrahedral, tree, tree;},
	doi = {10.1109/SMI.2005.47},
	author = {Danovaro,E. and De Floriani, Leila and Magillo,P. and Puppo,E. and Sobrero,D. and Sokolovsky,N.}
}
@conference {13198,
	title = {Kernel-based Bayesian filtering for object tracking},
	booktitle = {Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on},
	volume = {1},
	year = {2005},
	month = {2005/06//},
	pages = {227 - 234 vol. 1 - 227 - 234 vol. 1},
	abstract = {Particle filtering provides a general framework for propagating probability density functions in nonlinear and non-Gaussian systems. However, the algorithm is based on a Monte Carlo approach and sampling is a problematic issue, especially for high dimensional problems. This paper presents a new kernel-based Bayesian filtering framework, which adopts an analytic approach to better approximate and propagate density functions. In this framework, the techniques of density interpolation and density approximation are introduced to represent the likelihood and the posterior densities by Gaussian mixtures, where all parameters such as the number of mixands, their weight, mean, and covariance are automatically determined. The proposed analytic approach is shown to perform sampling more efficiently in high dimensional space. We apply our algorithm to real-time tracking problems, and demonstrate its performance on real video sequences as well as synthetic examples.},
	keywords = {approach;, approximation;, Bayes, Bayesian, Carlo, density, detection;, filtering;, functions;, Gaussian, interpolation;, kernel-based, methods;, mixtures;, Monte, nonGaussian, nonlinear, object, particle, probability, probability;, processes;, recognition;, sampling, sampling;, sequences;, system;, tracking;, video},
	doi = {10.1109/CVPR.2005.199},
	author = {Han,Bohyung and Zhu,Ying and Comaniciu, D. and Davis, Larry S.}
}
@conference {12280,
	title = {Measurement-based multipath multicast},
	booktitle = {INFOCOM 2005. 24th Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings IEEE},
	volume = {4},
	year = {2005},
	month = {2005/03//},
	pages = {2803 - 2808 vol. 4 - 2803 - 2808 vol. 4},
	abstract = {We propose a measurement-based routing algorithm to load balance intradomain traffic along multiple paths for multiple multicast sources. Multiple paths are established using application-layer overlaying. The proposed algorithm is able to converge under different network models, where each model reflects a different set of assumptions about the multicasting capabilities of the network. The algorithm is derived from simultaneous perturbation stochastic approximation and relies only on noisy estimates from measurements. Simulation results are presented to demonstrate the additional benefits obtained by incrementally increasing the multicasting capabilities.},
	keywords = {algorithm;, allocation;, application-layer, approximation, approximation;, balance, communication;, Convergence, convergence;, intradomain, load, measurement-based, methods;, Multicast, multipath, network, numerical, of, overlaying;, perturbation, processes;, resource, Routing, routing;, source;, Stochastic, techniques;, Telecommunication, theory;, traffic;},
	doi = {10.1109/INFCOM.2005.1498566},
	author = {Guven,T. and La,R.J. and Shayman,M.A. and Bhattacharjee, Bobby}
}
@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 {17790,
	title = {RDF aggregate queries and views},
	booktitle = {Data Engineering, 2005. ICDE 2005. Proceedings. 21st International Conference on},
	year = {2005},
	month = {2005/04//},
	pages = {717 - 728},
	abstract = {Resource description framework (RDF) is a rapidly expanding Web standard. RDF databases attempt to track the massive amounts of Web data and services available. In this paper, we study the problem of aggregate queries. We develop an algorithm to compute answers to aggregate queries over RDF databases and algorithms to maintain views involving those aggregates. Though RDF data can be stored in a standard relational DBMS (and hence we can execute standard relational aggregate queries and view maintenance methods on them), we show experimentally that our algorithms that operate directly on the RDF representation exhibit significantly superior performance.},
	keywords = {aggregate, databases;, DBMS;, description, framework;, languages;, Maintenance, methods;, processing;, queries;, query, RDF, relational, resource, standard;, standards;, view, Web},
	doi = {10.1109/ICDE.2005.121},
	author = {Hung,E. and Deng,Yu and V.S. Subrahmanian}
}
@conference {13190,
	title = {Segmentation and appearance model building from an image sequence},
	booktitle = {Image Processing, 2005. ICIP 2005. IEEE International Conference on},
	volume = {1},
	year = {2005},
	month = {2005/09//},
	pages = {I - 321-4 - I - 321-4},
	abstract = {In this paper we explore the problem of accurately segmenting a person from a video given only approximate location of that person. Unlike previous work which assumes that the appearance model is known in advance, we developed an iterative expectation-sampling (ES) algorithm for solving segmentation and appearance modeling simultaneously The appearance model is encoded with a kernel-based PDF defined in a joint color/path-length space. This appearance model remains unchanged during a short time period, although the object can articulate. Thus, we can perform the ES iteration not only for a single frame but also for an image sequence. The algorithm is iterative, but simple, efficient and gives visually good results.},
	keywords = {algorithm;, color-path-length, expectation-sampling, image, iterative, joint, kernel-based, methods;, PDF;, person, segmentation;, sequence;, sequences;, space;},
	doi = {10.1109/ICIP.2005.1529752},
	author = {Liang Zhao and Davis, Larry S.}
}
@article {14023,
	title = {Speaker Localization Using Excitation Source Information in Speech},
	journal = {Speech and Audio Processing, IEEE Transactions on},
	volume = {13},
	year = {2005},
	month = {2005/09//},
	pages = {751 - 761},
	abstract = {This paper presents the results of simulation and real room studies for localization of a moving speaker using information about the excitation source of speech production. The first step in localization is the estimation of time-delay from speech collected by a pair of microphones. Methods for time-delay estimation generally use spectral features that correspond mostly to the shape of vocal tract during speech production. Spectral features are affected by degradations due to noise and reverberation. This paper proposes a method for localizing a speaker using features that arise from the excitation source during speech production. Experiments were conducted by simulating different noise and reverberation conditions to compare the performance of the time-delay estimation and source localization using the proposed method with the results obtained using the spectrum-based generalized cross correlation (GCC) methods. The results show that the proposed method shows lower number of discrepancies in the estimated time-delays. The bias, variance and the root mean square error (RMSE) of the proposed method is consistently equal or less than the GCC methods. The location of a moving speaker estimated using the time-delays obtained by the proposed method are closer to the actual values, than those obtained by the GCC method.},
	keywords = {correlation, correlation;, cross, Delay, error, error;, estimation;, excitation, generalized, information;, localization;, mean, methods;, processing;, production;, root, source, speaker, speech, square, TIME},
	isbn = {1063-6676},
	doi = {10.1109/TSA.2005.851907},
	author = {Raykar,V.C. and Yegnanarayana,B. and Prasanna,S. R.M and Duraiswami, Ramani}
}
@conference {14034,
	title = {Computation of Green{\textquoteright}s function for finite-size photonic crystals by boundary element method},
	booktitle = {Antennas and Propagation Society International Symposium, 2004. IEEE},
	volume = {4},
	year = {2004},
	month = {2004/06//},
	pages = {4320 - 4323 Vol.4 - 4320 - 4323 Vol.4},
	abstract = {We have derived a new integral equation method for computing the Green{\textquoteright}s function for 2D electromagnetic wave propagation in a finite size photonic crystal. The method is also used for deriving the multipole expansions for the case of circular cylinders. This derivation is different from the ones in the literature. Our numerical results show an excellent agreement of the two algorithms. In the future we would like to expand the method to the numerical solution of the three-dimensional electromagnetic problem.},
	keywords = {2D, boundary, boundary-elements, circular, crystals;, cylinders;, electromagnetic, element, equation, equations;, expansions;, finite-size, function, function;, Green, Green{\textquoteright}s, integral, method;, methods;, multipole, photonic, propagation;, wave},
	doi = {10.1109/APS.2004.1330307},
	author = {Seydou,F. and Ramahi,O. and Duraiswami, Ramani and Seppdnen,T.}
}
@article {15384,
	title = {Finite-element computation of nonlinear magnetic diffusion and its effects when coupled to electrical, mechanical, and hydraulic systems},
	journal = {Magnetics, IEEE Transactions on},
	volume = {40},
	year = {2004},
	month = {2004/03//},
	pages = {537 - 540},
	abstract = {Finite elements are used to compute eddy currents and magnetic diffusion times in steel cylinders with nonlinear B{\textendash}H curves. Computations are made of diffusion times versus current in a typical axisymmetric magnetic actuator, showing good agreement with recently published approximate analytical formulas. The computed nonlinear diffusion times are then used to derive an equivalent resistor that is used in a model of an electrohydraulic system. The diffusion time causes delays in the coupled mechanical and hydraulic responses.},
	keywords = {actuator;, actuators;, analysis;, axisymmetric, B-H, coupled, currents;, curves;, cylinders;, diffusion, diffusion;, eddy, electrical, electrohydraulic, electrohydraulics;, electromagnetic, element, equivalent, finite, finite-element, flux;, hydraulic, magnetic, mechanical, methods;, nonlinear, resistor;, responses;, steel, system;, systems;, times;, transducers;},
	isbn = {0018-9464},
	doi = {10.1109/TMAG.2004.824591},
	author = {Brauer,J.R. and Mayergoyz, Issak D}
}
@conference {13216,
	title = {Iterative figure-ground discrimination},
	booktitle = {Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on},
	volume = {1},
	year = {2004},
	month = {2004/08//},
	pages = {67 - 70 Vol.1 - 67 - 70 Vol.1},
	abstract = {Figure-ground discrimination is an important problem in computer vision. Previous work usually assumes that the color distribution of the figure can be described by a low dimensional parametric model such as a mixture of Gaussians. However, such approach has difficulty selecting the number of mixture components and is sensitive to the initialization of the model parameters. In this paper, we employ non-parametric kernel estimation for color distributions of both the figure and background. We derive an iterative sampling-expectation (SE) algorithm for estimating the color, distribution and segmentation. There are several advantages of kernel-density estimation. First, it enables automatic selection of weights of different cues based on the bandwidth calculation from the image itself. Second, it does not require model parameter initialization and estimation. The experimental results on images of cluttered scenes demonstrate the effectiveness of the proposed algorithm.},
	keywords = {algorithm;, analysis;, Bandwidth, calculation;, Color, colour, Computer, density, dimensional, discrimination;, distribution;, distributions;, Estimation, estimation;, expectation, figure, Gaussian, ground, image, initialization;, iterative, Kernel, low, methods;, mixture;, model, model;, nonparametric, parameter, parametric, processes;, sampling, sampling;, segmentation, segmentation;, statistics;, theory;, vision;},
	doi = {10.1109/ICPR.2004.1334006},
	author = {Zhao, L. and Davis, Larry S.}
}
@conference {12683,
	title = {Multiple view tracking of humans modelled by kinematic chains},
	booktitle = {Image Processing, 2004. ICIP {\textquoteright}04. 2004 International Conference on},
	volume = {2},
	year = {2004},
	month = {2004/10//},
	pages = {1009 - 1012 Vol.2 - 1009 - 1012 Vol.2},
	abstract = {We use a kinematic chain to model human body motion. We estimate the kinematic chain motion parameters using pixel displacements calculated from video sequences obtained from multiple calibrated cameras to perform tracking. We derive a linear relation between the 2D motion of pixels in terms of the 3D motion parameters of various body parts using a perspective projection model for the cameras, a rigid body motion model for the base body and the kinematic chain model for the body parts. An error analysis of the estimator is provided, leading to an iterative algorithm for calculating the motion parameters from the pixel displacements. We provide experimental results to demonstrate the accuracy of our formulation. We also compare our iterative algorithm to the noniterative algorithm and discuss its robustness in the presence of noise.},
	keywords = {3D, algorithm;, analysis;, body, calibrated, cameras;, chain, displacement;, error, estimation;, human, image, iterative, kinematic, kinematics;, methods;, model;, MOTION, motion;, multiple, parameters;, perspective, Pixel, processing;, projection, sequences;, signal, tracking;, video, view},
	doi = {10.1109/ICIP.2004.1419472},
	author = {Sundaresan, A. and Chellapa, Rama and RoyChowdhury, R.}
}
@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}
}
@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 {12702,
	title = {Robust two-camera tracking using homography},
	booktitle = {Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP {\textquoteright}04). IEEE International Conference on},
	volume = {3},
	year = {2004},
	month = {2004/05//},
	pages = {iii - 1-4 vol.3 - iii - 1-4 vol.3},
	abstract = {The paper introduces a two view tracking method which uses the homography relation between the two views to handle occlusions. An adaptive appearance-based model is incorporated in a particle filter to realize robust visual tracking. Occlusion is detected using robust statistics. When there is occlusion in one view, the homography from this view to other views is estimated from previous tracking results and used to infer the correct transformation for the occluded view. Experimental results show the robustness of the two view tracker.},
	keywords = {Carlo, filter;, filters;, frame, framework;, homography;, image, method;, methods;, Monte, nonlinear, occlusions;, optical, particle, processing;, robust, sequences;, sequential, signal, statistics;, tracking, tracking;, two, two-camera, video, view, visual},
	doi = {10.1109/ICASSP.2004.1326466},
	author = {Yue,Zhanfeng and Zhou,S. K and Chellapa, Rama}
}
@conference {12705,
	title = {Vehicle detection and tracking using acoustic and video sensors},
	booktitle = {Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP {\textquoteright}04). IEEE International Conference on},
	volume = {3},
	year = {2004},
	month = {2004/05//},
	pages = {iii - 793-6 vol.3 - iii - 793-6 vol.3},
	abstract = {Multimodal sensing has attracted much attention in solving a wide range of problems, including target detection, tracking, classification, activity understanding, speech recognition, etc. In surveillance applications, different types of sensors, such as video and acoustic sensors, provide distinct observations of ongoing activities. We present a fusion framework using both video and acoustic sensors for vehicle detection and tracking. In the detection phase, a rough estimate of target direction-of-arrival (DOA) is first obtained using acoustic data through beam-forming techniques. This initial DOA estimate designates the approximate target location in video. Given the initial target position, the DOA is refined by moving target detection using the video data. Markov chain Monte Carlo techniques are then used for joint audio-visual tracking. A novel fusion approach has been proposed for tracking, based on different characteristics of audio and visual trackers. Experimental results using both synthetic and real data are presented. Improved tracking performance has been observed by fusing the empirical posterior probability density functions obtained using both types of sensors.},
	keywords = {acoustic, applications;, audio, audio-visual, beam-forming, Carlo, chain, density, detection;, direction-of-arrival, DOA, empirical, estimation;, framework;, functions;, fusion, fusion;, joint, Markov, methods;, Monte, moving, multimodal, object, optical, posterior, probability, probability;, processes;, processing;, sensing;, sensor, sensors;, signal, Surveillance, surveillance;, systems;, target, techniques;, tracking;, vehicle, video},
	doi = {10.1109/ICASSP.2004.1326664},
	author = {Chellapa, Rama and Qian,Gang and Qinfen Zheng}
}
@conference {14054,
	title = {A boundary element method for electromagnetic scattering by multiple cylinders},
	booktitle = {Antennas and Propagation Society International Symposium, 2003. IEEE},
	volume = {3},
	year = {2003},
	month = {2003/06//},
	pages = {516 - 519 vol.3 - 516 - 519 vol.3},
	abstract = {An integral equation approach is derived for an electromagnetic scattering from M multiple cylinders. The problem is two-dimensional and the integral equation is solved using the Nystrom method. We give numerical examples that illustrate the algorithm.},
	keywords = {algorithm;, boundary, boundary-elements, cylinders;, electromagnetic, element, equations;, Fredholm, integral, method;, methods;, multiple, Nystrom, scattering;, two-dimensional, type, wave},
	doi = {10.1109/APS.2003.1219899},
	author = {Seydou,F. and Duraiswami, Ramani and Seppanen,T.}
}
@conference {12303,
	title = {Construction of an efficient overlay multicast infrastructure for real-time applications},
	booktitle = {INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications. IEEE Societies},
	volume = {2},
	year = {2003},
	month = {2003/04/03/march},
	pages = {1521 - 1531 vol.2 - 1521 - 1531 vol.2},
	abstract = {This paper presents an overlay architecture where service providers deploy a set of service nodes (called MSNs) in the network to efficiently implement media-streaming applications. These MSNs are organized into an overlay and act as application-layer multicast forwarding entities for a set of clients. We present a decentralized scheme that organizes the MSNs into an appropriate overlay structure that is particularly beneficial for real-time applications. We formulate our optimization criterion as a "degree-constrained minimum average-latency problem" which is known to be NP-hard. A key feature of this formulation is that it gives a dynamic priority to different MSNs based on the size of its service set. Our proposed approach iteratively modifies the overlay tree using localized transformations to adapt with changing distribution of MSNs, clients, as well as network conditions. We show that a centralized greedy approach to this problem does not perform quite as well, while our distributed iterative scheme efficiently converges to near-optimal solutions.},
	keywords = {application-layer;, applications;, communication;, criterion;, decentralized, distributed, entities;, forwarding, infrastructure;, Internet;, iterative, media-streaming, methods;, MSN;, Multicast, nodes;, NP-hard;, OPTIMIZATION, overlay, real, real-time, scheme;, service, systems;, TIME},
	doi = {10.1109/INFCOM.2003.1208987},
	author = {Banerjee,S. and Kommareddy,C. and Kar,K. and Bhattacharjee, Bobby and Khuller, Samir}
}
@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.}
}
@conference {13239,
	title = {Mean-shift analysis using quasiNewton methods},
	booktitle = {Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on},
	volume = {2},
	year = {2003},
	month = {2003/09//},
	pages = {II - 447-50 vol.3 - II - 447-50 vol.3},
	abstract = {Mean-shift analysis is a general nonparametric clustering technique based on density estimation for the analysis of complex feature spaces. The algorithm consists of a simple iterative procedure that shifts each of the feature points to the nearest stationary point along the gradient directions of the estimated density function. It has been successfully applied to many applications such as segmentation and tracking. However, despite its promising performance, there are applications for which the algorithm converges too slowly to be practical. We propose and implement an improved version of the mean-shift algorithm using quasiNewton methods to achieve higher convergence rates. Another benefit of our algorithm is its ability to achieve clustering even for very complex and irregular feature-space topography. Experimental results demonstrate the efficiency and effectiveness of our algorithm.},
	keywords = {analysis;, classification;, clustering, clustering;, Convergence, density, estimation;, feature-space, image, irregular, iterative, Mean-shift, method;, methods;, Newton, nonparametric, pattern, procedure;, quasiNewton, rates;, segmentation;, technique;, topography;},
	doi = {10.1109/ICIP.2003.1246713},
	author = {Yang,C. and Duraiswami, Ramani and DeMenthon,D. and Davis, Larry S.}
}
@article {16897,
	title = {Properties of embedding methods for similarity searching in metric spaces},
	journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
	volume = {25},
	year = {2003},
	month = {2003/05//},
	pages = {530 - 549},
	abstract = {Complex data types-such as images, documents, DNA sequences, etc.-are becoming increasingly important in modern database applications. A typical query in many of these applications seeks to find objects that are similar to some target object, where (dis)similarity is defined by some distance function. Often, the cost of evaluating the distance between two objects is very high. Thus, the number of distance evaluations should be kept at a minimum, while (ideally) maintaining the quality of the result. One way to approach this goal is to embed the data objects in a vector space so that the distances of the embedded objects approximates the actual distances. Thus, queries can be performed (for the most part) on the embedded objects. We are especially interested in examining the issue of whether or not the embedding methods will ensure that no relevant objects are left out. Particular attention is paid to the SparseMap, FastMap, and MetricMap embedding methods. SparseMap is a variant of Lipschitz embeddings, while FastMap and MetricMap are inspired by dimension reduction methods for Euclidean spaces. We show that, in general, none of these embedding methods guarantee that queries on the embedded objects have no false dismissals, while also demonstrating the limited cases in which the guarantee does hold. Moreover, we describe a variant of SparseMap that allows queries with no false dismissals. In addition, we show that with FastMap and MetricMap, the distances of the embedded objects can be much greater than the actual distances. This makes it impossible (or at least impractical) to modify FastMap and MetricMap to guarantee no false dismissals.},
	keywords = {complex, contractiveness;, data, databases;, decomposition;, dimension, distance, distortion;, DNA, documents;, EMBEDDING, embeddings;, Euclidean, evaluations;, FastMap;, images;, Lipschitz, methods;, metric, MetricMap;, multimedia, processing;, query, reduction, search;, searching;, sequences;, similarity, singular, spaces;, SparseMap;, types;, value},
	isbn = {0162-8828},
	doi = {10.1109/TPAMI.2003.1195989},
	author = {Hjaltason,G. R and Samet, Hanan}
}
@conference {14052,
	title = {Three dimensional acoustic scattering from an M multilayered domain via an integral equation approach},
	booktitle = {Antennas and Propagation Society International Symposium, 2003. IEEE},
	volume = {1},
	year = {2003},
	month = {2003/06//},
	pages = {669 - 672 vol.1 - 669 - 672 vol.1},
	abstract = {An integral equation approach is derived for three dimensional acoustic scattering from an M multilayered domain. The integral equation is solved using the collocation method. To validate the method, we compare the exact and approximate results. The numerous matrix vector multiplications of our method may be thought a disadvantage. This problem can be overcome by using fast multiple methods where these operations are done very quickly.},
	keywords = {acoustic, collocation, dimensional, domain;, equation;, equations;, fast, inhomogeneous, integral, matrix, media;, method;, methods;, multilayered, multilayers;, multiple, multiplication;, multiplications;, scattering;, three, vector, wave},
	doi = {10.1109/APS.2003.1217547},
	author = {Seydou,F. and Duraiswami, Ramani and Seppanen,T.}
}
@conference {12765,
	title = {3D face reconstruction from video using a generic model},
	booktitle = {Multimedia and Expo, 2002. ICME {\textquoteright}02. Proceedings. 2002 IEEE International Conference on},
	volume = {1},
	year = {2002},
	month = {2002///},
	pages = {449 - 452 vol.1 - 449 - 452 vol.1},
	abstract = {Reconstructing a 3D model of a human face from a video sequence is an important problem in computer vision, with applications to recognition, surveillance, multimedia etc. However, the quality of 3D reconstructions using structure from motion (SfM) algorithms is often not satisfactory. One common method of overcoming this problem is to use a generic model of a face. Existing work using this approach initializes the reconstruction algorithm with this generic model. The problem with this approach is that the algorithm can converge to a solution very close to this initial value, resulting in a reconstruction which resembles the generic model rather than the particular face in the video which needs to be modeled. We propose a method of 3D reconstruction of a human face from video in which the 3D reconstruction algorithm and the generic model are handled separately. A 3D estimate is obtained purely from the video sequence using SfM algorithms without use of the generic model. The final 3D model is obtained after combining the SfM estimate and the generic model using an energy function that corrects for the errors in the estimate by comparing local regions in the two models. The optimization is done using a Markov chain Monte Carlo (MCMC) sampling strategy. The main advantage of our algorithm over others is that it is able to retain the specific features of the face in the video sequence even when these features are different from those of the generic model. The evolution of the 3D model through the various stages of the algorithm is presented.},
	keywords = {3D, algorithm;, algorithms;, analysis;, Carlo, chain, Computer, Face, from, function;, generic, human, image, Markov, MCMC, methods;, model;, Monte, MOTION, optimisation;, OPTIMIZATION, processes;, processing;, recognition;, reconstruction, reconstruction;, sampling;, sequence;, sequences;, SfM, signal, structure, surveillance;, video, vision;},
	doi = {10.1109/ICME.2002.1035815},
	author = {Chowdhury, A.R. and Chellapa, Rama and Krishnamurthy, S. and Vo, T.}
}
@conference {12758,
	title = {Bayesian structure from motion using inertial information},
	booktitle = {Image Processing. 2002. Proceedings. 2002 International Conference on},
	volume = {3},
	year = {2002},
	month = {2002///},
	pages = {III-425 - III-428 vol.3 - III-425 - III-428 vol.3},
	abstract = {A novel approach to Bayesian structure from motion (SfM) using inertial information and sequential importance sampling (SIS) is presented. The inertial information is obtained from camera-mounted inertial sensors and is used in the Bayesian SfM approach as prior knowledge of the camera motion in the sampling algorithm. Experimental results using both synthetic and real images show that, when inertial information is used, more accurate results can be obtained or the same estimation accuracy can be obtained at a lower cost.},
	keywords = {3D, analysis;, Bayes, Bayesian, camera, estimation;, image, images;, importance, inertial, information;, methods;, MOTION, motion;, parameter, processing;, real, reconstruction;, sampling;, scene, sensors;, sequence;, sequences;, sequential, signal, structure-from-motion;, synthetic, systems;, video},
	doi = {10.1109/ICIP.2002.1038996},
	author = {Qian,Gang and Chellapa, Rama and Qinfen Zheng}
}
@conference {13514,
	title = {Binarization of low quality text using a Markov random field model},
	booktitle = {Pattern Recognition, 2002. Proceedings. 16th International Conference on},
	volume = {3},
	year = {2002},
	month = {2002///},
	pages = {160 - 163 vol.3 - 160 - 163 vol.3},
	abstract = {Binarization techniques have been developed in the document analysis community for over 30 years and many algorithms have been used successfully. On the other hand, document analysis tasks are more and more frequently being applied to multimedia documents such as video sequences. Due to low resolution and lossy compression, the binarization of text included in the frames is a non-trivial task. Existing techniques work without a model of the spatial relationships in the image, which makes them less powerful. We introduce a new technique based on a Markov random field model of the document. The model parameters (clique potentials) are learned from training data and the binary image is estimated in a Bayesian framework. The performance is evaluated using commercial OCR software.},
	keywords = {analysis;, annealing;, Bayes, Bayesian, binarization;, computing;, distributions;, document, documents;, field;, Gibbs, image, low, Markov, method;, methods;, multimedia, optimization;, probability;, processes;, processing;, QUALITY, random, simulated, text},
	doi = {10.1109/ICPR.2002.1047819},
	author = {Wolf,C. and David Doermann}
}
@article {12752,
	title = {A generic approach to simultaneous tracking and verification in video},
	journal = {Image Processing, IEEE Transactions on},
	volume = {11},
	year = {2002},
	month = {2002/05//},
	pages = {530 - 544},
	abstract = {A generic approach to simultaneous tracking and verification in video data is presented. The approach is based on posterior density estimation using sequential Monte Carlo methods. Visual tracking, which is in essence a temporal correspondence problem, is solved through probability density propagation, with the density being defined over a proper state space characterizing the object configuration. Verification is realized through hypothesis testing using the estimated posterior density. In its most basic form, verification can be performed as follows. Given a measurement vector Z and two hypotheses H<sub>1</sub> and H0, we first estimate posterior probabilities P(H<sub>0</sub>|Z) and P(H<sub>1</sub>|Z), and then choose the one with the larger posterior probability as the true hypothesis. Several applications of the approach are illustrated by experiments devised to evaluate its performance. The idea is first tested on synthetic data, and then experiments with real video sequences are presented, illustrating vehicle tracking and verification, human (face) tracking and verification, facial feature tracking, and image sequence stabilization.},
	keywords = {approach;, Carlo, configuration;, correspondence, data;, density, density;, estimated, estimation;, evaluation;, extraction;, Face, facial, feature, generic, human, hypothesis, image, measurement, methods;, Monte, object, performance, posterior, probability, probability;, problem;, processing;, propagation;, recognition;, road, sequence, sequences;, sequential, signal, space;, stabilization;, state, synthetic, temporal, testing;, tracking;, vector;, vehicle, vehicles;, verification;, video, visual},
	isbn = {1057-7149},
	doi = {10.1109/TIP.2002.1006400},
	author = {Li,Baoxin and Chellapa, Rama}
}
@conference {12746,
	title = {A hierarchical approach for obtaining structure from two-frame optical flow},
	booktitle = {Motion and Video Computing, 2002. Proceedings. Workshop on},
	year = {2002},
	month = {2002/12//},
	pages = {214 - 219},
	abstract = {A hierarchical iterative algorithm is proposed for extracting structure from two-frame optical flow. The algorithm exploits two facts: one is that in many applications, such as face and gesture recognition, the depth variation of the visible surface of an object in a scene is small compared to the distance between the optical center and the object; the other is that the time aliasing problem is alleviated at the coarse level for any two-frame optical flow estimate so that the estimate tends to be more accurate. A hierarchical representation for the relationship between the optical flow, depth, and the motion parameters is derived, and the resulting non-linear system is iteratively solved through two linear subsystems. At the coarsest level, the surface of the object tends to be flat, so that the inverse depth tends to be a constant, which is used as the initial depth map. Inverse depth and motion parameters are estimated by the two linear subsystems at each level and the results are propagated to finer levels. Error analysis and experiments using both computer-rendered images and real images demonstrate the correctness and effectiveness of our algorithm.},
	keywords = {algorithm;, aliasing;, analysis;, computer-rendered, depth, depth;, error, estimation;, extraction;, Face, feature, flow;, gesture, hierarchical, image, images;, inverse, iterative, methods;, MOTION, nonlinear, optical, parameter, processing;, real, recognition;, sequences;, signal, structure-from-motion;, system;, systems;, TIME, two-frame, variation;, video},
	doi = {10.1109/MOTION.2002.1182239},
	author = {Liu,Haiying and Chellapa, Rama and Rosenfeld, A.}
}
@article {12748,
	title = {Optimal edge-based shape detection},
	journal = {Image Processing, IEEE Transactions on},
	volume = {11},
	year = {2002},
	month = {2002/11//},
	pages = {1209 - 1227},
	abstract = {We propose an approach to accurately detecting two-dimensional (2-D) shapes. The cross section of the shape boundary is modeled as a step function. We first derive a one-dimensional (1-D) optimal step edge operator, which minimizes both the noise power and the mean squared error between the input and the filter output. This operator is found to be the derivative of the double exponential (DODE) function, originally derived by Ben-Arie and Rao (1994). We define an operator for shape detection by extending the DODE filter along the shape{\textquoteright}s boundary contour. The responses are accumulated at the centroid of the operator to estimate the likelihood of the presence of the given shape. This method of detecting a shape is in fact a natural extension of the task of edge detection at the pixel level to the problem of global contour detection. This simple filtering scheme also provides a tool for a systematic analysis of edge-based shape detection. We investigate how the error is propagated by the shape geometry. We have found that, under general assumptions, the operator is locally linear at the peak of the response. We compute the expected shape of the response and derive some of its statistical properties. This enables us to predict both its localization and detection performance and adjust its parameters according to imaging conditions and given performance specifications. Applications to the problem of vehicle detection in aerial images, human facial feature detection, and contour tracking in video are presented.},
	keywords = {1D, 2D, aerial, analysis;, boundary, conditions;, contour, cross, detection;, DODE, double, edge, edge-based, error, error;, exponential, extraction;, facial, feature, filter, filter;, Filtering, function;, geometry;, global, human, images;, imaging, localization, mean, methods;, NOISE, operator;, optimal, optimisation;, output;, performance;, pixel;, power;, propagation;, properties;, section;, SHAPE, square, squared, statistical, step, theory;, tracking;, two-dimensional, vehicle, video;},
	isbn = {1057-7149},
	doi = {10.1109/TIP.2002.800896},
	author = {Moon, H. and Chellapa, Rama and Rosenfeld, A.}
}
@conference {12766,
	title = {Probabilistic recognition of human faces from video},
	booktitle = {Image Processing. 2002. Proceedings. 2002 International Conference on},
	volume = {1},
	year = {2002},
	month = {2002///},
	pages = {I-41 - I-44 vol.1 - I-41 - I-44 vol.1},
	abstract = {Most present face recognition approaches recognize faces based on still images. We present a novel approach to recognize faces in video. In that scenario, the face gallery may consist of still images or may be derived from a videos. For evidence integration we use classical Bayesian propagation over time and compute the posterior distribution using sequential importance sampling. The probabilistic approach allows us to handle uncertainties in a systematic manner. Experimental results using videos collected by NIST/USF and CMU illustrate the effectiveness of this approach in both still-to-video and video-to-video scenarios with appropriate model choices.},
	keywords = {Bayes, Bayesian, CMU;, distribution;, Face, faces;, gallery;, handling;, human, image, images;, importance, likelihood;, methods;, NIST/USF;, observation, posterior, probabilistic, probability;, processing;, propagation;, recognition;, sampling;, sequential, signal, still, Still-to-video, Uncertainty, video, Video-to-video},
	doi = {10.1109/ICIP.2002.1037954},
	author = {Chellapa, Rama and Kruger, V. and Zhou,Shaohua}
}
@conference {12756,
	title = {A robust algorithm for probabilistic human recognition from video},
	booktitle = {Pattern Recognition, 2002. Proceedings. 16th International Conference on},
	volume = {1},
	year = {2002},
	month = {2002///},
	pages = {226 - 229 vol.1 - 226 - 229 vol.1},
	abstract = {Human recognition from video requires solving the two tasks, recognition and tracking, simultaneously. This leads to a parameterized time series state space model, representing both motion and identity of the human. Sequential Monte Carlo (SMC) algorithms, like Condensation, can be developed to offer numerical solutions to this model. However in outdoor environments, the solution is more likely to diverge from the foreground, causing failures in both recognition and tracking. In this paper we propose an approach for tackling this problem by incorporating the constraint of temporal continuity in the observations. Experimental results demonstrate improvements over its Condensation counterpart.},
	keywords = {algorithm;, algorithms;, Carlo, continuity;, human, image, methods;, model;, Monte, parameterized, probabilistic, recognition;, robust, sequential, series, series;, space, state, state-space, temporal, TIME},
	doi = {10.1109/ICPR.2002.1044661},
	author = {Zhou,Shaohua and Chellapa, Rama}
}
@conference {13272,
	title = {A Smale-like decomposition for discrete scalar fields},
	booktitle = {Pattern Recognition, 2002. Proceedings. 16th International Conference on},
	volume = {1},
	year = {2002},
	month = {2002///},
	pages = {184 - 187 vol.1 - 184 - 187 vol.1},
	abstract = {In this paper we address the problem of representing the structure of the topology of a d-dimensional scalar field as a basis for constructing a multiresolution representation of the structure of such afield. To this aim, we define a discrete decomposition of a triangulated d-dimensional domain, on whose vertices the values of the field are given. We extend a Smale decomposition, defined by Thom (1949) and Smale (1960) for differentiable functions, to the discrete case, to what we call a Smale-like decomposition. We introduce the notion of discrete gradient vector field, which indicates the growth of the scalar field and matches with our decomposition. We sketch an algorithm for building a Smale-like decomposition and a graph-based representation of this decomposition. We present results for the case of two-dimensional fields.},
	keywords = {data, decomposition;, differentiable, discrete, domain;, field;, fields;, functions;, gradient, graph-based, methods;, multidimensional, multiresolution, representation;, scalar, Smale-like, structure, Topology, triangulated, vector, visualisation;},
	doi = {10.1109/ICPR.2002.1044644},
	author = {De Floriani, Leila and Mesmoudi,M. M. and Danovaro,E.}
}
