IEEE Transactions on Pattern Analysis and Machine Intelligence

Issue 11 • Nov. 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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  • Learning Outdoor Color Classification

    Publication Year: 2006, Page(s):1713 - 1723
    Cited by:  Papers (18)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1233 KB) | HTML iconHTML

    We present an algorithm for color classification with explicit illuminant estimation and compensation. A Gaussian classifier is trained with color samples from just one training image. Then, using a simple diagonal illumination model, the illuminants in a new scene that contains some of the surface classes seen in the training image are estimated in a maximum likelihood framework using the expecta... View full abstract»

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  • A Framework Toward Restoration of Writing Order from Single-Stroked Handwriting Image

    Publication Year: 2006, Page(s):1724 - 1737
    Cited by:  Papers (18)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2579 KB) | HTML iconHTML

    Restoration of writing order from a single-stroked handwriting image can be seen as the problem of finding the smoothest path in its graph representation. In this paper, a 3-phase approach to restore a writing order is proposed within the framework of the edge continuity relation (ECR). In the initial, local phase, in order to obtain possible ECRs at an even-degree node, a neural network is used f... View full abstract»

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  • A Bayesian Framework for Extracting Human Gait Using Strong Prior Knowledge

    Publication Year: 2006, Page(s):1738 - 1752
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2885 KB) | HTML iconHTML

    Extracting full-body motion of walking people from monocular video sequences in complex, real-world environments is an important and difficult problem, going beyond simple tracking, whose satisfactory solution demands an appropriate balance between use of prior knowledge and learning from data. We propose a consistent Bayesian framework for introducing strong prior knowledge into a system for extr... View full abstract»

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  • Fuzzy Markov Random Fields versus Chains for Multispectral Image Segmentation

    Publication Year: 2006, Page(s):1753 - 1767
    Cited by:  Papers (29)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3170 KB) | HTML iconHTML

    This paper deals with a comparison of recent statistical models based on fuzzy Markov random fields and chains for multispectral image segmentation. The fuzzy scheme takes into account discrete and continuous classes which model the imprecision of the hidden data. In this framework, we assume the dependence between bands and we express the general model for the covariance matrix. A fuzzy Markov ch... View full abstract»

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  • Random Walks for Image Segmentation

    Publication Year: 2006, Page(s):1768 - 1783
    Cited by:  Papers (840)  |  Patents (38)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1847 KB) | HTML iconHTML

    A novel method is proposed for performing multilabel, interactive image segmentation. Given a small number of pixels with user-defined (or predefined) labels, one can analytically and quickly determine the probability that a random walker starting at each unlabeled pixel will first reach one of the prelabeled pixels. By assigning each pixel to the label for which the greatest probability is calcul... View full abstract»

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  • Data Fusion and Multicue Data Matching by Diffusion Maps

    Publication Year: 2006, Page(s):1784 - 1797
    Cited by:  Papers (129)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2651 KB) | HTML iconHTML

    Data fusion and multicue data matching are fundamental tasks of high-dimensional data analysis. In this paper, we apply the recently introduced diffusion framework to address these tasks. Our contribution is three-fold: first, we present the Laplace-Beltrami approach for computing density invariant embeddings which are essential for integrating different sources of data. Second, we describe a refi... View full abstract»

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  • Evaluation of Stability of k-Means Cluster Ensembles with Respect to Random Initialization

    Publication Year: 2006, Page(s):1798 - 1808
    Cited by:  Papers (110)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2628 KB) | HTML iconHTML

    Many clustering algorithms, including cluster ensembles, rely on a random component. Stability of the results across different runs is considered to be an asset of the algorithm. The cluster ensembles considered here are based on k-means clusterers. Each clusterer is assigned a random target number of clusters, k and is started from a random initialization. Here, we use 10 artificial and 10 real d... View full abstract»

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  • Assessing Classifiers from Two Independent Data Sets Using ROC Analysis: A Nonparametric Approach

    Publication Year: 2006, Page(s):1809 - 1817
    Cited by:  Papers (17)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (657 KB) | HTML iconHTML

    This paper considers binary classification. We assess a classifier in terms of the area under the ROC curve (AUC). We estimate three important parameters, the conditional AUC (conditional on a particular training set) and the mean and variance of this AUC. We derive, as well, a closed form expression of the variance of the estimator of the AUG. This expression exhibits several components of varian... View full abstract»

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  • Optical Flow 3D Segmentation and Interpretation: A Variational Method with Active Curve Evolution and Level Sets

    Publication Year: 2006, Page(s):1818 - 1829
    Cited by:  Papers (23)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3540 KB) | HTML iconHTML

    This study investigates a variational, active curve evolution method for dense three-dimensional (3D) segmentation and interpretation of optical flow in an image sequence of a scene containing moving rigid objects viewed by a possibly moving camera. This method jointly performs 3D motion segmentation, 3D interpretation (recovery of 3D structure and motion), and optical flow estimation. The objecti... View full abstract»

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  • Dense Photometric Stereo: A Markov Random Field Approach

    Publication Year: 2006, Page(s):1830 - 1846
    Cited by:  Papers (32)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2509 KB) | HTML iconHTML

    We address the problem of robust normal reconstruction by dense photometric stereo, in the presence of complex geometry, shadows, highlight, transparencies, variable attenuation in light intensities, and inaccurate estimation in light directions. The input is a dense set of noisy photometric images, conveniently captured by using a very simple set-up consisting of a digital video camera, a reflect... View full abstract»

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  • A Framework for Weighted Fusion of Multiple Statistical Models of Shape and Appearance

    Publication Year: 2006, Page(s):1847 - 1857
    Cited by:  Papers (14)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1445 KB) | HTML iconHTML

    This paper presents a framework for weighted fusion of several active shape and active appearance models. The approach is based on the eigenspace fusion method proposed by Hall et al., which has been extended to fuse more than two weighted eigenspaces using unbiased mean and covariance matrix estimates. To evaluate the performance of fusion, a comparative assessment on segmentation precision as we... View full abstract»

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  • Three-Dimensional Face Recognition Using Shapes of Facial Curves

    Publication Year: 2006, Page(s):1858 - 1863
    Cited by:  Papers (113)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1505 KB) | HTML iconHTML

    We study shapes of facial surfaces for the purpose of face recognition. The main idea is to 1) represent surfaces by unions of level curves, called facial curves, of the depth function and 2) compare shapes of surfaces implicitly using shapes of facial curves. The latter is performed using a differential geometric approach that computes geodesic lengths between closed curves on a shape manifold. T... View full abstract»

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  • An Experimental Study on Pedestrian Classification

    Publication Year: 2006, Page(s):1863 - 1868
    Cited by:  Papers (287)  |  Patents (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1833 KB) | HTML iconHTML

    Detecting people in images is key for several important application domains in computer vision. This paper presents an in-depth experimental study on pedestrian classification; multiple feature-classifier combinations are examined with respect to their ROC performance and efficiency. We investigate global versus local and adaptive versus nonadaptive features, as exemplified by PCA coefficients, Ha... View full abstract»

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  • Dynamic Characterization of Cluster Structures for Robust and Inductive Support Vector Clustering

    Publication Year: 2006, Page(s):1869 - 1874
    Cited by:  Papers (83)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1571 KB) | HTML iconHTML

    A topological and dynamical characterization of the cluster structures described by the support vector clustering is developed. It is shown that each cluster can be decomposed into its constituent basin level cells and can be naturally extended to an enlarged clustered domain, which serves as a basis for inductive clustering. A simplified weighted graph preserving the topological structure of the ... View full abstract»

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  • Fast Agglomerative Clustering Using a k-Nearest Neighbor Graph

    Publication Year: 2006, Page(s):1875 - 1881
    Cited by:  Papers (50)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2779 KB) | HTML iconHTML

    We propose a fast agglomerative clustering method using an approximate nearest neighbor graph for reducing the number of distance calculations. The time complexity of the algorithm is improved from O(tauN2) to O(tauN log N) at the cost of a slight increase in distortion; here, tau denotes the lumber of nearest neighbor updates required at each iteration. According to the experiments, a ... View full abstract»

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  • The "Invaders' Algorithm: Range of Values Modulation for Accelerated Correlation

    Publication Year: 2006, Page(s):1882 - 1886
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (121 KB) | HTML iconHTML

    In this paper, we present an algorithm that allows the simultaneous calculation of several cross correlations. The algorithm works by shifting the range of values of different images/signals to occupy different orders of magnitude and then combining them to form a single composite image/signal. Because additional signals are placed in the space usually occupied by a single signal, we call this the... View full abstract»

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  • IEEE Computer Society - ReadyNotes

    Publication Year: 2006, Page(s): 1887
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  • Join the IEEE Computer Society - FREE Online Access to 1,300 self-paced IT training courses

    Publication Year: 2006, Page(s): 1888
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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
Sven Dickinson
University of Toronto
e-mail: sven@cs.toronto.edu