@conference {12548,
	title = {A Non-generative Approach for Face Recognition Across Aging},
	booktitle = {Biometrics: Theory, Applications and Systems, 2008. BTAS 2008. 2nd IEEE International Conference on},
	year = {2008},
	month = {2008/10//undefin},
	pages = {1 - 6},
	abstract = {Human faces undergo a lot of change in appearance as they age. Though facial aging has been studied for decades, it is only recently that attempts have been made to address the problem from a computational point of view. Most of these early efforts follow a simulation approach in which matching is performed by synthesizing face images at the target age. Given the innumerable different ways in which a face can potentially age, the synthesized aged image may not be similar to the actual aged image. In this paper, we bypass the synthesis step and directly analyze the drifts of facial features with aging from a purely matching perspective. Our analysis is based on the observation that facial appearance changes in a coherent manner as people age. We provide measures to capture this coherency in feature drifts. Illustrations and experimental results show the efficacy of such an approach for matching faces across age progression.},
	keywords = {appearance;nongenerative, approach;face, Face, image, matching;, recognition;facial, recognition;image, synthesis;face},
	doi = {10.1109/BTAS.2008.4699331},
	author = {Biswas,S. and Aggarwal,G. and Ramanathan,N. and Chellapa, Rama}
}
@conference {12589,
	title = {Symmetric Objects are Hardly Ambiguous},
	booktitle = {Computer Vision and Pattern Recognition, 2007. CVPR {\textquoteright}07. IEEE Conference on},
	year = {2007},
	month = {2007/06//},
	pages = {1 - 7},
	abstract = {Given any two images taken under different illumination conditions, there always exist a physically realizable object which is consistent with both the images even if the lighting in each scene is constrained to be a known point light source at infinity. In this paper, we show that images are much less ambiguous for the class of bilaterally symmetric Lambertian objects. In fact, the set of such objects can be partitioned into equivalence classes such that it is always possible to distinguish between two objects belonging to different equivalence classes using just one image per object. The conditions required for two objects to belong to the same equivalence class are very restrictive, thereby leading to the conclusion that images of symmetric objects are hardly ambiguous. The observation leads to an illumination-invariant matching algorithm to compare images of bilaterally symmetric Lambertian objects. Experiments on real data are performed to show the implications of the theoretical result even when the symmetry and Lambertian assumptions are not strictly satisfied.},
	keywords = {algorithm;symmetric, bilaterally, images;image, Lambertian, MATCHING, matching;, objects, objects;illumination-invariant, objects;symmetric, symmetric},
	doi = {10.1109/CVPR.2007.383289},
	author = {Aggarwal,G. and Biswas,S. and Chellapa, Rama}
}
@conference {13196,
	title = {Efficient mean-shift tracking via a new similarity measure},
	booktitle = {Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on},
	volume = {1},
	year = {2005},
	month = {2005/06//},
	pages = {176 - 183 vol. 1 - 176 - 183 vol. 1},
	abstract = {The mean shift algorithm has achieved considerable success in object tracking due to its simplicity and robustness. It finds local minima of a similarity measure between the color histograms or kernel density estimates of the model and target image. The most typically used similarity measures are the Bhattacharyya coefficient or the Kullback-Leibler divergence. In practice, these approaches face three difficulties. First, the spatial information of the target is lost when the color histogram is employed, which precludes the application of more elaborate motion models. Second, the classical similarity measures are not very discriminative. Third, the sample-based classical similarity measures require a calculation that is quadratic in the number of samples, making real-time performance difficult. To deal with these difficulties we propose a new, simple-to-compute and more discriminative similarity measure in spatial-feature spaces. The new similarity measure allows the mean shift algorithm to track more general motion models in an integrated way. To reduce the complexity of the computation to linear order we employ the recently proposed improved fast Gauss transform. This leads to a very efficient and robust nonparametric spatial-feature tracking algorithm. The algorithm is tested on several image sequences and shown to achieve robust and reliable frame-rate tracking.},
	keywords = {algorithm;, analysis;, Bhattacharyya, coefficient;, Color, colour, density, divergence;, estimates;, extraction;, fast, feature, frame-rate, Gauss, Gaussian, histograms;, image, Kernel, Kullback-Leibler, matching;, Mean-shift, measures;, nonparametric, processes;, sample-based, sequences;, similarity, spaces;, spatial-feature, tracking, tracking;, transform;},
	doi = {10.1109/CVPR.2005.139},
	author = {Yang,Changjiang and Duraiswami, Ramani and Davis, Larry S.}
}
@conference {13197,
	title = {Fast illumination-invariant background subtraction using two views: error analysis, sensor placement and applications},
	booktitle = {Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on},
	volume = {1},
	year = {2005},
	month = {2005/06//},
	pages = {1071 - 1078 vol. 1 - 1071 - 1078 vol. 1},
	abstract = {Background modeling and subtraction to detect new or moving objects in a scene is an important component of many intelligent video applications. Compared to a single camera, the use of multiple cameras leads to better handling of shadows, specularities and illumination changes due to the utilization of geometric information. Although the result of stereo matching can be used as the feature for detection, it has been shown that the detection process can be made much faster by a simple subtraction of the intensities observed at stereo-generated conjugate pairs in the two views. The methodology however, suffers from false and missed detections due to some geometric considerations. In this paper, we perform a detailed analysis of such errors. Then, we propose a sensor configuration that eliminates false detections. Algorithms are also proposed that effectively eliminate most detection errors due to missed detections, specular reflections and objects being geometrically close to the background. Experiments on several scenes illustrate the utility and enhanced performance of the proposed approach compared to existing techniques.},
	keywords = {analysis;, application;, background, cameras;, configuration;, DETECTION, detection;, error, error;, extraction;, false, feature, handling;, illumination-invariance;, image, intelligent, matching;, modeling;, object, placement;, processing;, sensor, sensors;, shadow, stereo, subtraction;, video},
	doi = {10.1109/CVPR.2005.155},
	author = {Lim,Ser-Nam and Mittal,A. and Davis, Larry S. and Paragios,N.}
}
@conference {13563,
	title = {Handwriting matching and its application to handwriting synthesis},
	booktitle = {Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on},
	year = {2005},
	month = {2005/09/01/aug},
	pages = {861 - 865 Vol. 2 - 861 - 865 Vol. 2},
	abstract = {Since it is extremely expensive to collect a large volume of handwriting samples, synthesized data are often used to enlarge the training set. We argue that, in order to generate good handwriting samples, a synthesis algorithm should learn the shape deformation characteristics of handwriting from real samples. In this paper, we present a point matching algorithm to learn the deformation, and apply it to handwriting synthesis. Preliminary experiments show the advantages of our approach.},
	keywords = {(artificial, deformation, deformation;, handwriting, image, intelligence);, learning, learning;, matching;, point, recognition;, sampling;, SHAPE, synthesis;},
	doi = {10.1109/ICDAR.2005.122},
	author = {Yefeng Zheng and David Doermann}
}
@conference {14845,
	title = {Using the inner-distance for classification of articulated shapes},
	booktitle = {Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on},
	volume = {2},
	year = {2005},
	month = {2005/06//},
	pages = {719 - 726 vol. 2 - 719 - 726 vol. 2},
	abstract = {We propose using the inner-distance between landmark points to build shape descriptors. The inner-distance is defined as the length of the shortest path between landmark points within the shape silhouette. We show that the inner-distance is articulation insensitive and more effective at capturing complex shapes with part structures than Euclidean distance. To demonstrate this idea, it is used to build a new shape descriptor based on shape contexts. After that, we design a dynamic programming based method for shape matching and comparison. We have tested our approach on a variety of shape databases including an articulated shape dataset, MPEG7 CE-Shape-1, Kimia silhouettes, a Swedish leaf database and a human motion silhouette dataset. In all the experiments, our method demonstrates effective performance compared with other algorithms.},
	keywords = {articulated, CE-Shape-1, classification;, database;, databases;, dataset;, descriptor;, dynamic, human, image, inner-distance;, Kimia, landmark, leaf, matching;, MOTION, MPEG7, points;, programming;, SHAPE, silhouette, silhouette;, Swedish, visual},
	doi = {10.1109/CVPR.2005.362},
	author = {Ling,H. and Jacobs, David W.}
}
@conference {13209,
	title = {Multi-level fast multipole method for thin plate spline evaluation},
	booktitle = {Image Processing, 2004. ICIP {\textquoteright}04. 2004 International Conference on},
	volume = {3},
	year = {2004},
	month = {2004/10//},
	pages = {1683 - 1686 Vol. 3 - 1683 - 1686 Vol. 3},
	abstract = {Image registration is an important problem in image processing and computer vision. Much recent work in image registration is on matching non-rigid deformations. Thin plate splines are an effective image registration method when the deformation between two images can be modeled as the bending of a thin metal plate on point constraints such that the topology is preserved (non-rigid deformation). However, because evaluating the computed TPS model at all the image pixels is computationally expensive, we need to speed it up. We introduce the use of multi-level fast muitipole method (MLFMM) for this purpose. Our contribution lies in the presentation of a clear and concise MLFMM framework for TPS, which will be useful for future application developments. The achieved speedup using MLFMM is an improvement from O(N<sup>2</sup>) to O(N log N). We show that the fast evaluation outperforms the brute force method while maintaining acceptable error bound.},
	keywords = {(mathematics);, Computer, deformation;, evaluation;, fast, image, MATCHING, matching;, metal, method;, multilevel, multipole, nonrigid, pixel;, plate, plate;, processing;, registration;, resolution;, spline, splines, thin, vision;},
	doi = {10.1109/ICIP.2004.1421395},
	author = {Zandifar,A. and Lim,S. and Duraiswami, Ramani and Gumerov, Nail A. and Davis, Larry S.}
}
@conference {12686,
	title = {Robust Bayesian cameras motion estimation using random sampling},
	booktitle = {Image Processing, 2004. ICIP {\textquoteright}04. 2004 International Conference on},
	volume = {2},
	year = {2004},
	month = {2004/10//},
	pages = {1361 - 1364 Vol.2 - 1361 - 1364 Vol.2},
	abstract = {In this paper, we propose an algorithm for robust 3D motion estimation of wide baseline cameras from noisy feature correspondences. The posterior probability density function of the camera motion parameters is represented by weighted samples. The algorithm employs a hierarchy coarse-to-fine strategy. First, a coarse prior distribution of camera motion parameters is estimated using the random sample consensus scheme (RANSAC). Based on this estimate, a refined posterior distribution of camera motion parameters can then be obtained through importance sampling. Experimental results using both synthetic and real image sequences indicate the efficacy of the proposed algorithm.},
	keywords = {3D, baseline, Bayesian, CAMERAS, cameras;, coarse-to-fine, consensus, density, estimation;, feature, function;, hierarchy, image, images;, importance, matching;, MOTION, posterior, probability, probability;, processing;, random, RANSAC;, real, realistic, sample, sampling;, scheme;, sequences;, stereo, strategy;, synthetic, wide},
	doi = {10.1109/ICIP.2004.1419754},
	author = {Qian, G. and Chellapa, Rama and Qinfen Zheng}
}
@conference {13210,
	title = {Uncalibrated stereo rectification for automatic 3D surveillance},
	booktitle = {Image Processing, 2004. ICIP {\textquoteright}04. 2004 International Conference on},
	volume = {2},
	year = {2004},
	month = {2004/10//},
	pages = {1357 - 1360 Vol.2 - 1357 - 1360 Vol.2},
	abstract = {We describe a stereo rectification method suitable for automatic 3D surveillance. We take advantage of the fact that in a typical urban scene, there is ordinarily a small number of dominant planes. Given two views of the scene, we align a dominant plane in one view with the other. Conjugate epipolar lines between the reference view and plane-aligned image become geometrically identical and can be added to the rectified image pair line by line. Selecting conjugate epipolar lines to cover the whole image is simplified since they are geometrically identical. In addition, the polarities of conjugate epipolar lines are automatically preserved by plane alignment, which simplifies stereo matching.},
	keywords = {3D, AUTOMATIC, conjugate, epipolar, image, lines;, matching;, method;, processing;, rectification, scene;, stereo, surveillance;, uncalibrated, urban},
	doi = {10.1109/ICIP.2004.1419753},
	author = {Lim,S.-N. and Mittal,A. and Davis, Larry S. and Paragios,N.}
}
@article {12699,
	title = {Wide baseline image registration with application to 3-D face modeling},
	journal = {Multimedia, IEEE Transactions on},
	volume = {6},
	year = {2004},
	month = {2004/06//},
	pages = {423 - 434},
	abstract = {Establishing correspondence between features in two images of the same scene taken from different viewing angles is a challenging problem in image processing and computer vision. However, its solution is an important step in many applications like wide baseline stereo, three-dimensional (3-D) model alignment, creation of panoramic views, etc. In this paper, we propose a technique for registration of two images of a face obtained from different viewing angles. We show that prior information about the general characteristics of a face obtained from video sequences of different faces can be used to design a robust correspondence algorithm. The method works by matching two-dimensional (2-D) shapes of the different features of the face (e.g., eyes, nose etc.). A doubly stochastic matrix, representing the probability of match between the features, is derived using the Sinkhorn normalization procedure. The final correspondence is obtained by minimizing the probability of error of a match between the entire constellation of features in the two sets, thus taking into account the global spatial configuration of the features. The method is applied for creating holistic 3-D models of a face from partial representations. Although this paper focuses primarily on faces, the algorithm can also be used for other objects with small modifications.},
	keywords = {2D, 3D, algorithm;, baseline, biometrics;, Computer, configuration;, correspondence, doubly, error, extraction;, Face, feature, holistic, image, matching;, matrix;, minimization;, modeling;, models;, normalization, probability, probability;, procedure;, processes;, processing;, recognition;, registration;, representation;, sequences;, shapes;, Sinkhorn, spatial, statistics;, Stochastic, video, vision;, wide},
	isbn = {1520-9210},
	doi = {10.1109/TMM.2004.827511},
	author = {Roy-Chowdhury, A.K. and Chellapa, Rama and Keaton, T.}
}
@conference {13217,
	title = {Window-based, discontinuity preserving stereo},
	booktitle = {Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on},
	volume = {1},
	year = {2004},
	month = {2004/07/02/june},
	pages = {I-66 - I-73 Vol.1 - I-66 - I-73 Vol.1},
	abstract = {Traditionally, the problem of stereo matching has been addressed either by a local window-based approach or a dense pixel-based approach using global optimization. In this paper we present an algorithm which combines window-based local matching into a global optimization framework. Our local matching algorithm assumes that local windows can have at most two disparities. Under this assumption, the local matching can be performed very efficiently using graph cuts. The global matching is formulated as minimization of an energy term that takes into account the matching constraints induced by the local stereo algorithm. Fast, approximate minimization of this energy is achieved through graph cuts. The key feature of our algorithm is that it preserves discontinuities both during the local as well as global matching phase.},
	keywords = {algorithm;, approach;, based, cuts;, dense, discontinuity, global, graph, image, local, MATCHING, matching;, minimisation;, optimization;, Pixel, preserving, processing;, stereo, theory;, window},
	doi = {10.1109/CVPR.2004.1315015},
	author = {Agrawal,M. and Davis, Larry S.}
}
@conference {16894,
	title = {Depth-first k-nearest neighbor finding using the MaxNearestDist estimator},
	booktitle = {Image Analysis and Processing, 2003.Proceedings. 12th International Conference on},
	year = {2003},
	month = {2003/09//},
	pages = {486 - 491},
	abstract = {Similarity searching is an important task when trying to find patterns in applications which involve mining different types of data such as images, video, time series, text documents, DNA sequences, etc. Similarity searching often reduces to finding the k nearest neighbors to a query object. A description is given of how to use an estimate of the maximum possible distance at which a nearest neighbor can be found to prune the search process in a depth-first branch-and-bound k-nearest neighbor finding algorithm. Using the MaxNearestDist estimator (Larsen, S. and Kanal, L.N., 1986) in the depth-first k-nearest neighbor algorithm provides a middle ground between a pure depth-first and a best-first k-nearest neighbor algorithm.},
	keywords = {branch-and-bound, data, depth-first, distance;, DNA, documents;, estimation;, estimator;, finding;, images;, k-nearest, matching;, maximum, MaxNearestDist, mining;, neighbor, parameter, pattern, possible, process;, processing;, query, search, searching;, sequences;, series;, similarity, text, TIME, tree, video;},
	doi = {10.1109/ICIAP.2003.1234097},
	author = {Samet, Hanan}
}
@conference {14051,
	title = {Electromagnetic scattering from a multilayered cylindrical waveguide},
	booktitle = {Antennas and Propagation Society International Symposium, 2003. IEEE},
	volume = {3},
	year = {2003},
	month = {2003/06//},
	pages = {332 - 335 vol.3 - 332 - 335 vol.3},
	abstract = {This paper is devoted to electromagnetic scattering from an N multilayered circular cylinder. We consider waveguides in the z direction; that is, we look for the solution of Maxwell equations along the z direction. We assume a dielectric core and derive a mode matching approach for solving the problem. A numerical result is presented that illustrates the algorithm.},
	keywords = {circular, core;, cylinder;, cylindrical, dielectric, dielectric-loaded, electromagnetic, EM, equations;, matching;, Maxwell, mode, multilayered, scattering;, theory;, wave, waveguide, waveguide;, waveguides;},
	doi = {10.1109/APS.2003.1219855},
	author = {Seydou,F. and Duraiswami, Ramani and Seppanen,T.}
}
@conference {13240,
	title = {Exemplar-based tracking and recognition of arm gestures},
	booktitle = {Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the 3rd International Symposium on},
	volume = {2},
	year = {2003},
	month = {2003/09//},
	pages = {656 - 661 Vol.2 - 656 - 661 Vol.2},
	abstract = {This paper presents a probabilistic exemplar-based framework for recognizing gestures. The approach is based on representing each gesture as a sequence of learned body poses. The gestures are recognized through a probabilistic framework for matching these body poses and for imposing temporal constrains between different poses. Matching individual poses to image data is performed using a probabilistic formulation for edge matching to obtain a likelihood measurement for each individual pose. The paper introduces a correspondence-free weighted matching scheme for edge templates that emphasize discriminating features in the matching. The weighting does not require establishing correspondences between the different pose models. The probabilistic framework also imposes temporal constrains between different pose through a learned hidden Markov model (HMM) of each gesture.},
	keywords = {arm, constrains;, correspondence-free, edge, exemplar-based, framework;, gesture, hidden, HMM;, image, logic;, Markov, MATCHING, matching;, model;, models;, probabilistic, recognition;, scheme;, segmentation;, temporal, tracking;, weighted},
	doi = {10.1109/ISPA.2003.1296358},
	author = {Elgammal,A. and Shet,V. and Yacoob,Yaser and Davis, Larry S.}
}
@conference {13247,
	title = {Learning dynamics for exemplar-based gesture recognition},
	booktitle = {Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on},
	volume = {1},
	year = {2003},
	month = {2003/06//},
	pages = {I-571 - I-578 vol.1 - I-571 - I-578 vol.1},
	abstract = {This paper addresses the problem of capturing the dynamics for exemplar-based recognition systems. Traditional HMM provides a probabilistic tool to capture system dynamics and in exemplar paradigm, HMM states are typically coupled with the exemplars. Alternatively, we propose a non-parametric HMM approach that uses a discrete HMM with arbitrary states (decoupled from exemplars) to capture the dynamics over a large exemplar space where a nonparametric estimation approach is used to model the exemplar distribution. This reduces the need for lengthy and non-optimal training of the HMM observation model. We used the proposed approach for view-based recognition of gestures. The approach is based on representing each gesture as a sequence of learned body poses (exemplars). The gestures are recognized through a probabilistic framework for matching these body poses and for imposing temporal constraints between different poses using the proposed non-parametric HMM.},
	keywords = {arbitrary, body, by, Computer, constraint;, detection;, discrete, distribution, dynamics;, edge, estimation;, example;, exemplar, exemplar-based, extraction;, feature, framework;, gesture, gesture;, hidden, HMM;, human, image, learning, Markov, matching;, model;, models;, motion;, nonparametric, pose, probabilistic, recognition;, sequence;, space;, state;, statistics;, system, temporal, tool;, view-based, vision;},
	doi = {10.1109/CVPR.2003.1211405},
	author = {Elgammal,A. and Shet,V. and Yacoob,Yaser and Davis, Larry S.}
}
@conference {16896,
	title = {Simultaneous pose and correspondence determination using line features},
	booktitle = {Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on},
	volume = {2},
	year = {2003},
	month = {2003/06//},
	pages = {II-424 - II-431 vol.2 - II-424 - II-431 vol.2},
	abstract = {We present a new robust line matching algorithm for solving the model-to-image registration problem. Given a model consisting of 3D lines and a cluttered perspective image of this model, the algorithm simultaneously estimates the pose of the model and the correspondences of model lines to image lines. The algorithm combines softassign for determining correspondences and POSIT for determining pose. Integrating these algorithms into a deterministic annealing procedure allows the correspondence and pose to evolve from initially uncertain values to a joint local optimum. This research extends to line features the SoftPOSIT algorithm proposed recently for point features. Lines detected in images are typically more stable than points and are less likely to be produced by clutter and noise, especially in man-made environments. Experiments on synthetic and real imagery with high levels of clutter, occlusion, and noise demonstrate the robustness of the algorithm.},
	keywords = {algorithm;, algorithms;, annealing;, clutter;, cluttered, Computer, correspondence, detection;, determination;, deterministic, environment;, extraction;, feature, feature;, image, image;, imagery;, images;, joint, line, local, man-made, MATCHING, matching;, measurement;, model-to-image, noise;, occlusion;, optimum;, perspective, point, pose, position, problem;, processing;, real, realistic, registration, simulated, softassign;, SoftPOSIT, stereo, synthetic, vision;},
	doi = {10.1109/CVPR.2003.1211499},
	author = {David,P. and DeMenthon,D. and Duraiswami, Ramani and Samet, Hanan}
}
@conference {12733,
	title = {Statistical shape theory for activity modeling},
	booktitle = {Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP {\textquoteright}03). 2003 IEEE International Conference on},
	volume = {3},
	year = {2003},
	month = {2003/04//},
	pages = {III - 493-6 vol.3 - III - 493-6 vol.3},
	abstract = {Monitoring activities in a certain region from video data is an important surveillance problem. The goal is to learn the pattern of normal activities and detect unusual ones by identifying activities that deviate appreciably from the typical ones. We propose an approach using statistical shape theory based on the shape model of D.G. Kendall et al. (see "Shape and Shape Theory", John Wiley and Sons, 1999). In a low resolution video, each moving object is best represented as a moving point mass or particle. In this case, an activity can be defined by the interactions of all or some of these moving particles over time. We model this configuration of the particles by a polygonal shape formed from the locations of the points in a frame and the activity by the deformation of the polygons in time. These parameters are learned for each typical activity. Given a test video sequence, an activity is classified as abnormal if the probability for the sequence (represented by the mean shape and the dynamics of the deviations), given the model, is below a certain threshold The approach gives very encouraging results in surveillance applications using a single camera and is able to identify various kinds of abnormal behavior.},
	keywords = {abnormal, activities, activity, analysis;, behavior;, classification;, data;, image, mass;, matching;, modeling;, monitoring;, moving, normal, particle;, pattern, pattern;, point, polygonal, probability;, problem;, processing;, sequence;, sequences;, SHAPE, shape;, signal, statistical, Surveillance, surveillance;, theory;, video},
	doi = {10.1109/ICASSP.2003.1199519},
	author = {Vaswani, N. and Chowdhury, A.R. and Chellapa, Rama}
}
@conference {18156,
	title = {A recognition algorithm for Chinese characters in diverse fonts},
	booktitle = {Image Processing. 2002. Proceedings. 2002 International Conference on},
	volume = {3},
	year = {2002},
	month = {2002/06//},
	pages = {981 - 984 vol.3 - 981 - 984 vol.3},
	abstract = {The paper proposes an algorithm for recognizing Chinese characters in many diverse fonts including Song, Fang, Kai, Hei, Yuan, Lishu, Weibei and Xingkai. The algorithm is based on features derived from peripheral direction contributions and utilizes a set of dictionaries. A 3-level matching is first performed with respect to each dictionary. The distance measures associated with these matches are then fed into a central discriminator to output the final recognition result. We propose a new multi-dictionary matching algorithm for use in the central discriminator that utilizes estimated information of neighborhood fonts. Experiments have been performed on a practical OCR software system whose recognition kernel is based on the proposed algorithm. Fast and accurate recognition has been accomplished both in title recognition, involving all of the 8 fonts, and in main-body recognition, that usually involves only the first 4 most commonly used fonts.},
	keywords = {algorithm;, central, character, Chinese, contributions;, direction, discriminator;, diverse, fonts;, image, interfaces;, LANGUAGE, MATCHING, matching;, multi-dictionary, natural, OCR, optical, peripheral, recognition, recognition;, sets;, software, system;},
	doi = {10.1109/ICIP.2002.1039139},
	author = {Wu,Xianli and M. Wu}
}
@conference {12747,
	title = {Wide baseline image registration using prior information},
	booktitle = {Multimedia Signal Processing, 2002 IEEE Workshop on},
	year = {2002},
	month = {2002/12//},
	pages = {37 - 40},
	abstract = {Establishing correspondence between features in two images of the same scene taken from different viewing angles in a challenging problem in image processing and computer vision. However, its solution is an important step in many applications like wide baseline stereo, 3D model alignment, creation of panoramic views etc. In this paper, we propose a technique for registration of two images of a face obtained from different viewing angles. We show that prior information about the general characteristics of a face obtained from video sequences of different faces can be used to design a robust correspondence algorithm. The method works by matching 2D shapes of the different features of the face. A doubly stochastic matrix, representing the probability of match between the features, is derived using the Sinkhorn normalization procedure. The final correspondence is obtained by minimizing the probability of error of a match between the entire constellations of features in the two sets, thus taking into account the global spatial configuration of the features. The method is applied for creating holistic 3D models of a face from partial representations. Although this paper focuses primarily on faces, the algorithm can also be used for other objects with small modifications.},
	keywords = {2D, 3D, algorithm;, alignment;, angles;, baseline, Computer, configuration;, constellation;, correspondence, creation;, doubly, error, extraction;, Face, feature, global, holistic, image, images;, matching;, matrix;, model, models;, normalization, panoramic, probability;, procedure;, processes;, processing;, registration;, robust, sequences;, SHAPE, signal, Sinkhorn, spatial, statistics;, stereo;, Stochastic, video, view, viewing, vision;, wide},
	doi = {10.1109/MMSP.2002.1203242},
	author = {Chowdhury, AM and Chellapa, Rama and Keaton, T.}
}
@conference {15207,
	title = {Efficient minimum cost matching using quadrangle inequality},
	booktitle = {Foundations of Computer Science, 1992. Proceedings., 33rd Annual Symposium on},
	year = {1992},
	month = {1992/10//},
	pages = {583 - 592},
	abstract = {The authors present efficient algorithms for finding a minimum cost perfect matching, and for solving the transportation problem in bipartite graphs, G = (Red cup; Blue, Red times; Blue), where |Red| = n, |Blue| = m, n les; m, and the cost function obeys the quadrangle inequality. The first results assume that all the red points and all the blue points lie on a curve that is homeomorphic to either a line or a circle and the cost function is given by the Euclidean distance along the curve. They present a linear time algorithm for the matching problem. They generalize the method to solve the corresponding transportation problem in O((m+n)log(m+n)) time. The next result is an O(n log m) algorithm for minimum cost matching when the cost array is a bitonic Monge array. An example of this is when the red points lie on one straight line and the blue points lie on another straight line (that is not necessarily parallel to the first one). Finally, they provide a weakly polynomial algorithm for the transportation problem in which the associated cost array is a bitonic Monge array},
	keywords = {algorithm;, array;, bipartite, bitonic, blue, complexity;, computational, cost, distance;, Euclidean, function;, geometry;, graph, graphs;, inequality;, linear, MATCHING, matching;, minimisation;, minimum, Monge, perfect, points;, polynomial, problem;, quadrangle, red, theory;, TIME, transportation, transportation;, weakly},
	doi = {10.1109/SFCS.1992.267793},
	author = {Aggarwal,A. and Bar-Noy,A. and Khuller, Samir and Kravets,D. and Schieber,B.}
}
