IEEE Transactions on Pattern Analysis and Machine Intelligence

Issue 4 • April 2004

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Displaying Results 1 - 14 of 14
  • IEEE Transactions on Pattern Analysis and Machine Intelligence - Table of Contents

    Publication Year: 2004, Page(s): 01
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  • IEEE Transactions on Pattern Analysis and Machine Intelligence

    Publication Year: 2004, Page(s): 0_2
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  • Introduction of new Associate Editor

    Publication Year: 2004, Page(s): 433
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  • A similarity-based robust clustering method

    Publication Year: 2004, Page(s):434 - 448
    Cited by:  Papers (107)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1537 KB) | HTML iconHTML

    This paper presents an alternating optimization clustering procedure called a similarity-based clustering method (SCM). It is an effective and robust approach to clustering on the basis of a total similarity objective function related to the approximate density shape estimation. We show that the data points in SCM can self-organize local optimal cluster number and volumes without using cluster val... View full abstract»

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  • Appearance-based face recognition and light-fields

    Publication Year: 2004, Page(s):449 - 465
    Cited by:  Papers (130)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1798 KB) | HTML iconHTML

    Arguably the most important decision to be made when developing an object recognition algorithm is selecting the scene measurements or features on which to base the algorithm. In appearance-based object recognition, the features are chosen to be the pixel intensity values in an image of the object. These pixel intensities correspond directly to the radiance of light emitted from the object along c... View full abstract»

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  • Motion estimation using statistical learning theory

    Publication Year: 2004, Page(s):466 - 478
    Cited by:  Papers (17)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1746 KB) | HTML iconHTML

    This paper describes a novel application of statistical learning theory (SLT) to single motion estimation and tracking. The problem of motion estimation can be related to statistical model selection, where the goal is to select one (correct) motion model from several possible motion models, given finite noisy samples. SLT, also known as Vapnik-Chervonenkis (VC), theory provides analytic generaliza... View full abstract»

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  • Layered motion segmentation and depth ordering by tracking edges

    Publication Year: 2004, Page(s):479 - 494
    Cited by:  Papers (59)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1647 KB) | HTML iconHTML

    This paper presents a new Bayesian framework for motion segmentation ividing a frame from an image sequence into layers representing different moving objects - by tracking edges between frames. Edges are found using the Canny edge detector, and the expectation-maximization algorithm is then used to fit motion models to these edges and also to calculate the probabilities of the edges obe... View full abstract»

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  • Error-tolerant sign retrieval using visual features and maximum a posteriori estimation

    Publication Year: 2004, Page(s):495 - 508
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1872 KB) | HTML iconHTML

    This paper proposes an efficient error-tolerant approach to retrieving sign words from a Taiwanese Sign Language (TSL) database. This database is tagged with visual gesture features and organized as a multilist code tree. These features are defined in terms of the visual characteristics of sign gestures by which they are indexed for sign retrieval and displayed using an anthropomorphic interface. ... View full abstract»

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  • Multiple light source detection

    Publication Year: 2004, Page(s):509 - 514
    Cited by:  Papers (16)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (622 KB) | HTML iconHTML

    This paper presents the V2R algorithm, a novel method for multiple light source detection using a Lambertian sphere as a calibration object. The algorithm segments the image of the sphere into regions that are each illuminated by a single virtual light and subtracts the virtual lights of adjacent regions to estimate the light source vectors. The algorithm uses all pixels within a region to form a ... View full abstract»

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  • An eigenspace projection clustering method for inexact graph matching

    Publication Year: 2004, Page(s):515 - 519
    Cited by:  Papers (83)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (562 KB) | HTML iconHTML

    In this paper, we show how inexact graph matching (that is, the correspondence between sets of vertices of pairs of graphs) can be solved using the renormalization of projections of the vertices (as defined in this case by their connectivities) into the joint eigenspace of a pair of graphs and a form of relational clustering. An important feature of this eigenspace renormalization projection clust... View full abstract»

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  • Estimating degradation model parameters using neighborhood pattern distributions: an optimization approach

    Publication Year: 2004, Page(s):520 - 524
    Cited by:  Papers (14)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (855 KB) | HTML iconHTML

    Noise models are crucial for designing image restoration algorithms, generating synthetic training data, and predicting algorithm performance. There are two related but distinct estimation scenarios. The first is model calibration, where it is assumed that the input ideal bitmap and the output of the degradation process are both known. The second is the general estimation problem, where only the i... View full abstract»

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  • Fast k-nearest neighbor classification using cluster-based trees

    Publication Year: 2004, Page(s):525 - 528
    Cited by:  Papers (56)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (446 KB) | HTML iconHTML

    Most fast k-nearest neighbor (k-NN) algorithms exploit metric properties of distance measures for reducing computation cost and a few can work effectively on both metric and nonmetric measures. We propose a cluster-based tree algorithm to accelerate k-NN classification without any presuppositions about the metric form and properties of a dissimilarity measure. A mechanism of early decision making ... View full abstract»

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  • TPAMI: Information for authors

    Publication Year: 2004, Page(s): 03
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  • IEEE Computer Society Information

    Publication Year: 2004, Page(s): 0_4
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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