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IEEE Transactions on Pattern Analysis and Machine Intelligence

Issue 9 • Date Sept. 2008

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Displaying Results 1 - 18 of 18
  • [Front cover]

    Publication Year: 2008, Page(s): c1
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  • [Inside front cover]

    Publication Year: 2008, Page(s): c2
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  • Introduction of New Associate Editors

    Publication Year: 2008, Page(s):1505 - 1506
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  • Global Models for the Orientation Field of Fingerprints: An Approach Based on Quadratic Differentials

    Publication Year: 2008, Page(s):1507 - 1519
    Cited by:  Papers (30)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (4653 KB) | HTML iconHTML

    Quadratic differentials naturally define analytic orientation fields on planar surfaces. We propose to model orientation fields of fingerprints by specifying quadratic differentials. Models for all fingerprint classes such as arches, loops and whorls are laid out. These models are parametrised by few, geometrically interpretable parameters which are invariant under Euclidean motions. We demonstrat... View full abstract»

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  • Design of Multimodal Dissimilarity Spaces for Retrieval of Video Documents

    Publication Year: 2008, Page(s):1520 - 1533
    Cited by:  Papers (16)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3855 KB) | HTML iconHTML

    The paper proposes a novel representation space for multimodal information, enabling fast and efficient retrieval of video data. We suggest describing the documents not directly by selected multimodal features (audio, visual, or text) but rather by considering cross-document similarities relative to their multimodal characteristics. This idea leads us to propose a particular form of dissimilarity ... View full abstract»

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  • Feature Selection with Kernel Class Separability

    Publication Year: 2008, Page(s):1534 - 1546
    Cited by:  Papers (90)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2844 KB) | HTML iconHTML

    Classification can often benefit from efficient feature selection. However, the presence of linearly nonseparable data, quick response requirement, small sample problem and noisy features makes the feature selection quite challenging. In this work, a class separability criterion is developed in a high-dimensional kernel space, and feature selection is performed by the maximization of this criterio... View full abstract»

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  • Out-of-Sample Extrapolation of Learned Manifolds

    Publication Year: 2008, Page(s):1547 - 1556
    Cited by:  Papers (12)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1988 KB) | HTML iconHTML

    We investigate the problem of extrapolating the embedding of a manifold learned from finite samples to novel out-of-sample data. We concentrate on the manifold learning method called Maximum Variance Unfolding (MVU) for which the extrapolation problem is still largely unsolved. Taking the perspective of MVU learning being equivalent to Kernel PCA, our problem reduces to extending a kernel matrix g... View full abstract»

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  • Query by Transduction

    Publication Year: 2008, Page(s):1557 - 1571
    Cited by:  Papers (26)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2522 KB) | HTML iconHTML

    There has been recently a growing interest in the use of transductive inference for learning. We expand here the scope of transductive inference to active learning in a stream-based setting. Towards that end this paper proposes Query-by-Transduction (QBT) as a novel active learning algorithm. QBT queries the label of an example based on the p-values obtained using transduction. We show that QBT is... View full abstract»

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  • Bittracker—A Bitmap Tracker for Visual Tracking under Very General Conditions

    Publication Year: 2008, Page(s):1572 - 1588
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2615 KB) | HTML iconHTML

    This paper addresses the problem of visual tracking under very general conditions: a possibly non-rigid target whose appearance may drastically change over time; general camera motion; a 3D scene; and no a priori information except initialization. This is in contrast to the vast majority of trackers which rely on some limited model in which, for example, the target's appearance is known a priori o... View full abstract»

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  • Inferring Segmented Dense Motion Layers Using 5D Tensor Voting

    Publication Year: 2008, Page(s):1589 - 1602
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3689 KB) | HTML iconHTML

    We present a novel local spatiotemporal approach to produce motion segmentation and dense temporal trajectories from an image sequence. A common representation of image sequences is a 3D spatiotemporal volume, (x,y,t), and its corresponding mathematical formalism is the fiber bundle. However, directly enforcing the spatiotemporal smoothness constraint is difficult in the fiber bundle representatio... View full abstract»

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  • Multiple-View Geometry Under the {$L_infty$}-Norm

    Publication Year: 2008, Page(s):1603 - 1617
    Cited by:  Papers (102)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1634 KB) | HTML iconHTML

    This paper presents a new framework for solving geometric structure and motion problems based on the Linfin-norm. Instead of using the common sum-of-squares cost function, that is, the L2-norm, the model-fitting errors are measured using the Linfin-norm. Unlike traditional methods based on L2, our framework allows for the efficient computation of global ... View full abstract»

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  • Class-Based Feature Matching Across Unrestricted Transformations

    Publication Year: 2008, Page(s):1618 - 1631
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3474 KB) | HTML iconHTML

    We develop a novel method for class-based feature matching across large changes in viewing conditions. The method is based on the property that when objects share a similar part, the similarity is preserved across viewing conditions. Given a feature and a training set of object images, we first identify the subset of objects that share this feature. The transformation of the feature's appearance a... View full abstract»

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  • Randomized Clustering Forests for Image Classification

    Publication Year: 2008, Page(s):1632 - 1646
    Cited by:  Papers (120)  |  Patents (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2420 KB) | HTML iconHTML

    Some of the most effective recent methods for content-based image classification work by quantizing image descriptors, and accumulating histograms of the resulting visual word codes. Large numbers of descriptors and large codebooks are required for good results and this becomes slow using k-means. We introduce Extremely Randomized Clustering Forests-ensembles of randomly created clustering trees-a... View full abstract»

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  • Effective Proximity Retrieval by Ordering Permutations

    Publication Year: 2008, Page(s):1647 - 1658
    Cited by:  Papers (40)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3266 KB) | HTML iconHTML

    We introduce a new probabilistic proximity search algorithm for range and A"-nearest neighbor (A"-NN) searching in both coordinate and metric spaces. Although there exist solutions for these problems, they boil down to a linear scan when the space is intrinsically high dimensional, as is the case in many pattern recognition tasks. This, for example, renders the A"-NN approach to classification rat... View full abstract»

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  • Measuring Spatiotemporal Dependencies in Bivariate Temporal Random Sets with Applications to Cell Biology

    Publication Year: 2008, Page(s):1659 - 1671
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2494 KB) | HTML iconHTML

    Analyzing spatiotemporal dependencies between different types of events is highly relevant to many biological phenomena (e.g., signaling and trafficking), especially as advances in probes and microscopy have facilitated the imaging of dynamic processes in living cells. For many types of events, the segmented areas can overlap spatially and temporally, forming random clumps. In this paper, we model... View full abstract»

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  • Principal Component Analysis Based on L1-Norm Maximization

    Publication Year: 2008, Page(s):1672 - 1680
    Cited by:  Papers (167)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3023 KB) | HTML iconHTML

    A method of principal component analysis (PCA) based on a new L1-norm optimization technique is proposed. Unlike conventional PCA which is based on L2-norm, the proposed method is robust to outliers because it utilizes L1-norm which is less sensitive to outliers. It is invariant to rotations as well. The proposed L1-norm optimization technique is intuitive, simple, and easy to implement. It is als... View full abstract»

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  • TPAMI Information for authors

    Publication Year: 2008, Page(s): c3
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  • [Back cover]

    Publication Year: 2008, 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