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IEEE Transactions on Pattern Analysis and Machine Intelligence

Issue 6 • Date June 2006

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Displaying Results 1 - 22 of 22
  • [Front cover]

    Publication Year: 2006, Page(s): c1
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  • [Inside front cover]

    Publication Year: 2006, Page(s): c2
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  • Introduction of New Associate Editors

    Publication Year: 2006, Page(s): 849
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  • Fingerprint matching based on global comprehensive similarity

    Publication Year: 2006, Page(s):850 - 862
    Cited by:  Papers (22)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3534 KB) | HTML iconHTML

    This paper introduces a novel algorithm based on global comprehensive similarity with three steps. To describe the Euclidean space-based relative features among minutiae, we first build a minutia-simplex that contains a pair of minutiae as well as their associated textures, with its transformation-variant and invariant relative features employed for the comprehensive similarity measurement and par... View full abstract»

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  • Improved gait recognition by gait dynamics normalization

    Publication Year: 2006, Page(s):863 - 876
    Cited by:  Papers (143)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2644 KB) | HTML iconHTML

    Potential sources for gait biometrics can be seen to derive from two aspects: gait shape and gait dynamics. We show that improved gait recognition can be achieved after normalization of dynamics and focusing on the shape information. We normalize for gait dynamics using a generic walking model, as captured by a population hidden Markov model (pHMM) defined for a set of individuals. The states of t... View full abstract»

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  • Dynamic cluster formation using level set methods

    Publication Year: 2006, Page(s):877 - 889
    Cited by:  Papers (26)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3140 KB) | HTML iconHTML

    Density-based clustering has the advantages for: 1) allowing arbitrary shape of cluster and 2) not requiring the number of clusters as input. However, when clusters touch each other, both the cluster centers and cluster boundaries (as the peaks and valleys of the density distribution) become fuzzy and difficult to determine. We introduce the notion of cluster intensity function (CIF) which capture... View full abstract»

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  • Robust and accurate vectorization of line drawings

    Publication Year: 2006, Page(s):890 - 904
    Cited by:  Papers (45)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3133 KB) | HTML iconHTML

    This paper presents a method for vectorizing the graphical parts of paper-based line drawings. The method consists of separating the input binary image into layers of homogeneous thickness, skeletonizing each layer, segmenting the skeleton by a method based on random sampling, and simplifying the result. The segmentation method is robust with a best bound of 50 percent noise reached for indefinite... View full abstract»

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  • A model-based approach for estimating human 3D poses in static images

    Publication Year: 2006, Page(s):905 - 916
    Cited by:  Papers (53)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2461 KB) | HTML iconHTML

    Estimating human body poses in static images is important for many image understanding applications including semantic content extraction and image database query and retrieval. This problem is challenging due to the presence of clutter in the image, ambiguities in image observation, unknown human image boundary, and high-dimensional state space due to the complex articulated structure of the huma... View full abstract»

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  • From sample similarity to ensemble similarity: probabilistic distance measures in reproducing kernel Hilbert space

    Publication Year: 2006, Page(s):917 - 929
    Cited by:  Papers (76)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2231 KB) | HTML iconHTML Multimedia Media

    This paper addresses the problem of characterizing ensemble similarity from sample similarity in a principled manner. Using a reproducing kernel as a characterization of sample similarity, we suggest a probabilistic distance measure in the reproducing kernel Hilbert space (RKHS) as the ensemble similarity. Assuming normality in the RKHS, we derive analytic expressions for probabilistic distance me... View full abstract»

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  • Sequential Monte Carlo for Bayesian matching of objects with occlusions

    Publication Year: 2006, Page(s):930 - 941
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2808 KB) | HTML iconHTML

    We consider the problem of locating instances of a known object in a novel scene by matching the fiducial features of the object. The appearance of the features and the shape of the object are modeled separately and combined in a Bayesian framework. In this paper, we present a novel matching scheme based on sequential Monte Carlo, in which the features are matched sequentially, utilizing the infor... View full abstract»

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  • Nearest neighbors by neighborhood counting

    Publication Year: 2006, Page(s):942 - 953
    Cited by:  Papers (52)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3519 KB) | HTML iconHTML

    Finding nearest neighbors is a general idea that underlies many artificial intelligence tasks, including machine learning, data mining, natural language understanding, and information retrieval. This idea is explicitly used in the k-nearest neighbors algorithm (kNN), a popular classification method. In this paper, this idea is adopted in the development of a general methodology, neighborhood count... View full abstract»

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  • Learning shape-classes using a mixture of tree-unions

    Publication Year: 2006, Page(s):954 - 967
    Cited by:  Papers (39)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1327 KB) | HTML iconHTML

    This paper poses the problem of tree-clustering as that of fitting a mixture of tree unions to a set of sample trees. The tree-unions are structures from which the individual data samples belonging to a cluster can be obtained by edit operations. The distribution of observed tree nodes in each cluster sample is assumed to be governed by a Bernoulli distribution. The clustering method is designed t... View full abstract»

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  • Stereo using monocular cues within the tensor voting framework

    Publication Year: 2006, Page(s):968 - 982
    Cited by:  Papers (19)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3200 KB) | HTML iconHTML

    We address the fundamental problem of matching in two static images. The remaining challenges are related to occlusion and lack of texture. Our approach addresses these difficulties within a perceptual organization framework, considering both binocular and monocular cues. Initially, matching candidates for all pixels are generated by a combination of matching techniques. The matching candidates ar... View full abstract»

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  • Two-view multibody structure-and-motion with outliers through model selection

    Publication Year: 2006, Page(s):983 - 995
    Cited by:  Papers (32)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3352 KB) | HTML iconHTML

    Multibody structure-and-motion (MSaM) is the problem in establishing the multiple-view geometry of several views of a 3D scene taken at different times, where the scene consists of multiple rigid objects moving relative to each other. We examine the case of two views. The setting is the following: Given are a set of corresponding image points in two images, which originate from an unknown number o... View full abstract»

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  • Face recognition using IPCA-ICA algorithm

    Publication Year: 2006, Page(s):996 - 1000
    Cited by:  Papers (48)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (641 KB) | HTML iconHTML

    In this paper, a fast incremental principal non-Gaussian directions analysis algorithm, called IPCA-ICA, is introduced. This algorithm computes the principal components of a sequence of image vectors incrementally without estimating the covariance matrix (so covariance-free) and at the same time transforming these principal components to the independent directions that maximize the non-Gaussianity... View full abstract»

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  • Improving multiclass pattern recognition by the combination of two strategies

    Publication Year: 2006, Page(s):1001 - 1006
    Cited by:  Papers (57)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2479 KB) | HTML iconHTML

    We present a new method of multiclass classification based on the combination of one-vs-all method and a modification of one-vs-one method. This combination of one-vs-all and one-vs-one methods proposed enforces the strength of both methods. A study of the behavior of the two methods identifies some of the sources of their failure. The performance of a classifier can be improved if the two methods... View full abstract»

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  • Discriminant ECOC: a heuristic method for application dependent design of error correcting output codes

    Publication Year: 2006, Page(s):1007 - 1012
    Cited by:  Papers (81)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2026 KB) | HTML iconHTML

    We present a heuristic method for learning error correcting output codes matrices based on a hierarchical partition of the class space that maximizes a discriminative criterion. To achieve this goal, the optimal codeword separation is sacrificed in favor of a maximum class discrimination in the partitions. The creation of the hierarchical partition set is performed using a binary tree. As a result... View full abstract»

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  • Bayesian feature and model selection for Gaussian mixture models

    Publication Year: 2006, Page(s):1013 - 1018
    Cited by:  Papers (62)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1071 KB) | HTML iconHTML

    We present a Bayesian method for mixture model training that simultaneously treats the feature selection and the model selection problem. The method is based on the integration of a mixture model formulation that takes into account the saliency of the features and a Bayesian approach to mixture learning that can be used to estimate the number of mixture components. The proposed learning algorithm ... View full abstract»

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  • A 3D shape constraint on video

    Publication Year: 2006, Page(s):1018 - 1023
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (912 KB) | HTML iconHTML

    We propose to combine the information from multiple motion fields by enforcing a constraint on the surface normals (3D shape) of the scene in view. The fact that the shape vectors in the different views are related only by rotation can be formulated as a rank = 3 constraint. This constraint is implemented in an algorithm which solves 3D motion and structure estimation as a practical constrained mi... View full abstract»

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  • IEEE Computer Society celebrates two 60-year anniversaries

    Publication Year: 2006, Page(s): 1024
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  • TPAMI Information for authors

    Publication Year: 2006, Page(s): c3
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  • [Back cover]

    Publication Year: 2006, Page(s): c4
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Aims & Scope

The IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) is published monthly. Its editorial board strives to present most important research results in areas within TPAMI's scope.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
David A. Forsyth
University of Illinois
e-mail: daf@illinois.edu