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IEEE Transactions on Pattern Analysis and Machine Intelligence

Issue 8 • Date Aug. 2010

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Displaying Results 1 - 20 of 20
  • [Front cover]

    Publication Year: 2010, Page(s): c1
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  • [Inside front cover]

    Publication Year: 2010, Page(s): c2
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  • Editor's Note

    Publication Year: 2010, Page(s):1345 - 1346
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  • A Variational Approach to Degraded Document Enhancement

    Publication Year: 2010, Page(s):1347 - 1361
    Cited by:  Papers (11)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (4151 KB) | HTML iconHTML

    The goal of this paper is to correct bleed-through in degraded documents using a variational approach. The variational model is adapted using an estimated background according to the availability of the verso side of the document image. Furthermore, for the latter case, a more advanced model based on a global control, the flow field, is introduced. The solution of each resulting model is obtained ... View full abstract»

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  • Accurate, Dense, and Robust Multiview Stereopsis

    Publication Year: 2010, Page(s):1362 - 1376
    Cited by:  Papers (297)  |  Patents (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (6255 KB) | HTML iconHTML

    This paper proposes a novel algorithm for multiview stereopsis that outputs a dense set of small rectangular patches covering the surfaces visible in the images. Stereopsis is implemented as a match, expand, and filter procedure, starting from a sparse set of matched keypoints, and repeatedly expanding these before using visibility constraints to filter away false matches. The keys to the performa... View full abstract»

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  • Efficient Multilevel Eigensolvers with Applications to Data Analysis Tasks

    Publication Year: 2010, Page(s):1377 - 1391
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1768 KB) | HTML iconHTML

    Multigrid solvers proved very efficient for solving massive systems of equations in various fields. These solvers are based on iterative relaxation schemes together with the approximation of the “smooth” error function on a coarser level (grid). We present two efficient multilevel eigensolvers for solving massive eigenvalue problems that emerge in data analysis tasks. The first solve... View full abstract»

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  • Fusion Moves for Markov Random Field Optimization

    Publication Year: 2010, Page(s):1392 - 1405
    Cited by:  Papers (39)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2591 KB) | HTML iconHTML

    The efficient application of graph cuts to Markov Random Fields (MRFs) with multiple discrete or continuous labels remains an open question. In this paper, we demonstrate one possible way of achieving this by using graph cuts to combine pairs of suboptimal labelings or solutions. We call this combination process the fusion move. By employing recently developed graph-cut-based algorithms (so-called... View full abstract»

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  • Image Segmentation with a Unified Graphical Model

    Publication Year: 2010, Page(s):1406 - 1425
    Cited by:  Papers (24)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (5904 KB) | HTML iconHTML

    We propose a unified graphical model that can represent both the causal and noncausal relationships among random variables and apply it to the image segmentation problem. Specifically, we first propose to employ Conditional Random Field (CRF) to model the spatial relationships among image superpixel regions and their measurements. We then introduce a multilayer Bayesian Network (BN) to model the c... View full abstract»

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  • Layered Graph Matching with Composite Cluster Sampling

    Publication Year: 2010, Page(s):1426 - 1442
    Cited by:  Papers (11)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (4918 KB) | HTML iconHTML

    This paper presents a framework of layered graph matching for integrating graph partition and matching. The objective is to find an unknown number of corresponding graph structures in two images. We extract discriminative local primitives from both images and construct a candidacy graph whose vertices are matching candidates (i.e., a pair of primitives) and whose edges are either negative for mutu... View full abstract»

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  • Online Empirical Evaluation of Tracking Algorithms

    Publication Year: 2010, Page(s):1443 - 1458
    Cited by:  Papers (15)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3932 KB) | HTML iconHTML Multimedia Media

    Evaluation of tracking algorithms in the absence of ground truth is a challenging problem. There exist a variety of approaches for this problem, ranging from formal model validation techniques to heuristics that look for mismatches between track properties and the observed data. However, few of these methods scale up to the task of visual tracking, where the models are usually nonlinear and comple... View full abstract»

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  • Point Set Registration via Particle Filtering and Stochastic Dynamics

    Publication Year: 2010, Page(s):1459 - 1473
    Cited by:  Papers (16)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2085 KB) | HTML iconHTML

    In this paper, we propose a particle filtering approach for the problem of registering two point sets that differ by a rigid body transformation. Typically, registration algorithms compute the transformation parameters by maximizing a metric given an estimate of the correspondence between points across the two sets of interest. This can be viewed as a posterior estimation problem, in which the cor... View full abstract»

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  • Revisiting the Linear Programming Relaxation Approach to Gibbs Energy Minimization and Weighted Constraint Satisfaction

    Publication Year: 2010, Page(s):1474 - 1488
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1531 KB) | HTML iconHTML

    We present a number of contributions to the LP relaxation approach to weighted constraint satisfaction (= Gibbs energy minimization). We link this approach to many works from constraint programming, which relation has so far been ignored in machine vision and learning. While the approach has been mostly considered only for binary constraints, we generalize it to n-ary constraints in a simple and n... View full abstract»

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  • The Patch Transform

    Publication Year: 2010, Page(s):1489 - 1501
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (4169 KB) | HTML iconHTML Multimedia Media

    The patch transform represents an image as a bag of overlapping patches sampled on a regular grid. This representation allows users to manipulate images in the patch domain, which then seeds the inverse patch transform to synthesize modified images. Possible modifications include the spatial locations of patches, the size of the output image, or the pool of patches from which an image is reconstru... View full abstract»

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  • Iris Recognition: On the Segmentation of Degraded Images Acquired in the Visible Wavelength

    Publication Year: 2010, Page(s):1502 - 1516
    Cited by:  Papers (30)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (5387 KB) | HTML iconHTML

    Iris recognition imaging constraints are receiving increasing attention. There are several proposals to develop systems that operate in the visible wavelength and in less constrained environments. These imaging conditions engender acquired noisy artifacts that lead to severely degraded images, making iris segmentation a major issue. Having observed that existing iris segmentation methods tend to f... View full abstract»

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  • On the Complexity of Discrete Feature Selection for Optimal Classification

    Publication Year: 2010, Page(s):1517 - 1522
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (388 KB) | HTML iconHTML

    Consider a classification problem involving only discrete features that are represented as random variables with some prescribed discrete sample space. In this paper, we study the complexity of two feature selection problems. The first problem consists in finding a feature subset of a given size k that has minimal Bayes risk. We show that for any increasing ordering of the Bayes risks of the featu... View full abstract»

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  • Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters

    Publication Year: 2010, Page(s):1522 - 1528
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2173 KB) | HTML iconHTML Multimedia Media

    Adapting the hyperparameters of support vector machines (SVMs) is a challenging model selection problem, especially when flexible kernels are to be adapted and data are scarce. We present a coherent framework for regularized model selection of 1-norm soft margin SVMs for binary classification. It is proposed to use gradient-ascent on a likelihood function of the hyperparameters. The likelihood fun... View full abstract»

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  • The UBIRIS.v2: A Database of Visible Wavelength Iris Images Captured On-the-Move and At-a-Distance

    Publication Year: 2010, Page(s):1529 - 1535
    Cited by:  Papers (70)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2085 KB) | HTML iconHTML

    The iris is regarded as one of the most useful traits for biometric recognition and the dissemination of nationwide iris-based recognition systems is imminent. However, currently deployed systems rely on heavy imaging constraints to capture near infrared images with enough quality. Also, all of the publicly available iris image databases contain data correspondent to such imaging constraints and t... View full abstract»

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  • Call for Papers: Automatic Face and Gesture Recognition FG2011

    Publication Year: 2010, Page(s): 1536
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  • TPAMI Information for authors

    Publication Year: 2010, Page(s): c3
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  • [Back cover]

    Publication Year: 2010, 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