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IEEE Transactions on Pattern Analysis and Machine Intelligence

Issue 4 • Date April 2006

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Displaying Results 1 - 21 of 21
  • [Front cover]

    Publication Year: 2006, Page(s):c1 - c11
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  • [Inside front cover]

    Publication Year: 2006, Page(s):c2 - c22
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  • Metric learning for text documents

    Publication Year: 2006, Page(s):497 - 508
    Cited by:  Papers (32)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1589 KB) | HTML iconHTML

    Many algorithms in machine learning rely on being given a good distance metric over the input space. Rather than using a default metric such as the Euclidean metric, it is desirable to obtain a metric based on the provided data. We consider the problem of learning a Riemannian metric associated with a given differentiable manifold and a set of points. Our approach to the problem involves choosing ... View full abstract»

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  • Graph partitioning active contours (GPAC) for image segmentation

    Publication Year: 2006, Page(s):509 - 521
    Cited by:  Papers (46)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3463 KB) | HTML iconHTML

    In this paper, we introduce new types of variational segmentation cost functions and associated active contour methods that are based on pairwise similarities or dissimilarities of the pixels. As a solution to a minimization problem, we introduce a new curve evolution framework, the graph partitioning active contours (GPAC). Using global features, our curve evolution is able to produce results clo... View full abstract»

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  • Variational Bayes for continuous hidden Markov models and its application to active learning

    Publication Year: 2006, Page(s):522 - 532
    Cited by:  Papers (25)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1158 KB) | HTML iconHTML

    In this paper, we present a variational Bayes (VB) framework for learning continuous hidden Markov models (CHMMs), and we examine the VB framework within active learning. Unlike a maximum likelihood or maximum a posteriori training procedure, which yield a point estimate of the CHMM parameters, VB-based training yields an estimate of the full posterior of the model parameters. This is particularly... View full abstract»

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  • A genetic algorithm using hyper-quadtrees for low-dimensional k-means clustering

    Publication Year: 2006, Page(s):533 - 543
    Cited by:  Papers (45)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2625 KB) | HTML iconHTML

    The k-means algorithm is widely used for clustering because of its computational efficiency. Given n points in d-dimensional space and the number of desired clusters k, k-means seeks a set of k-cluster centers so as to minimize the sum of the squared Euclidean distance between each point and its nearest cluster center. However, the algorithm is very sensitive to the initial selection of centers an... View full abstract»

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  • Selection of generative models in classification

    Publication Year: 2006, Page(s):544 - 554
    Cited by:  Papers (12)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1969 KB) | HTML iconHTML

    This paper is concerned with the selection of a generative model for supervised classification. Classical criteria for model selection assess the fit of a model rather than its ability to produce a low classification error rate. A new criterion, the Bayesian entropy criterion (BEC), is proposed. This criterion takes into account the decisional purpose of a model by minimizing the integrated classi... View full abstract»

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  • Sparse representation for coarse and fine object recognition

    Publication Year: 2006, Page(s):555 - 567
    Cited by:  Papers (11)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3125 KB) | HTML iconHTML

    This paper offers a sparse, multiscale representation of objects. It captures the object appearance by selection from a very large dictionary of Gaussian differential basis functions. The learning procedure results from the matching pursuit algorithm, while the recognition is based on polynomial approximation to the bases, turning image matching into a problem of polynomial evaluation. The method ... View full abstract»

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  • Shapeme histogram projection and matching for partial object recognition

    Publication Year: 2006, Page(s):568 - 577
    Cited by:  Papers (21)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2005 KB) | HTML iconHTML

    Histograms of shape signature or prototypical shapes, called shapemes, have been used effectively in previous work for 2D/3D shape matching and recognition. We extend the idea of shapeme histogram to recognize partially observed query objects from a database of complete model objects. We propose representing each model object as a collection of shapeme histograms and match the query histogram to t... View full abstract»

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  • A discriminative learning framework with pairwise constraints for video object classification

    Publication Year: 2006, Page(s):578 - 593
    Cited by:  Papers (23)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3704 KB) | HTML iconHTML

    To deal with the problem of insufficient labeled data in video object classification, one solution is to utilize additional pairwise constraints that indicate the relationship between two examples, i.e., whether these examples belong to the same class or not. In this paper, we propose a discriminative learning approach which can incorporate pairwise constraints into a conventional margin-based lea... View full abstract»

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  • One-shot learning of object categories

    Publication Year: 2006, Page(s):594 - 611
    Cited by:  Papers (339)  |  Patents (17)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (6015 KB) | HTML iconHTML

    Learning visual models of object categories notoriously requires hundreds or thousands of training examples. We show that it is possible to learn much information about a category from just one, or a handful, of images. The key insight is that, rather than learning from scratch, one can take advantage of knowledge coming from previously learned categories, no matter how different these categories ... View full abstract»

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  • A shape-from-shading method of polyhedral objects using prior information

    Publication Year: 2006, Page(s):612 - 624
    Cited by:  Papers (12)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2618 KB) | HTML iconHTML

    We propose a new method for recovering the 3D shape of a polyhedral object from its single 2D image using the shading information contained in the image and the prior information on the object. In a strict sense, we cannot recover the shape of a polyhedron from an incorrect line drawing, even if it is practically almost correct. In order to overcome this problem, we propose a flexible face positio... View full abstract»

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  • Motion analysis of articulated objects from monocular images

    Publication Year: 2006, Page(s):625 - 636
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1380 KB) | HTML iconHTML

    This paper presents a new method of motion analysis of articulated objects from feature point correspondences over monocular perspective images without imposing any constraints on motion. An articulated object is modeled as a kinematic chain consisting of joints and links, and its 3D joint positions are estimated within a scale factor using the connection relationship of two links over two or thre... View full abstract»

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  • Custom-built moments for edge location

    Publication Year: 2006, Page(s):637 - 642
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (664 KB) | HTML iconHTML

    We present a general construction of functions whose moments serve to locate and parametrize step edges within an image. Previous use of moments to locate edges was limited to functions supported on a circular region, but our method allows the use of "custom-designed" functions supported on circles, rectangles, or any desired shape, and with graphs whose shape may be chosen with great freedom. We ... View full abstract»

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  • Robust point matching for nonrigid shapes by preserving local neighborhood structures

    Publication Year: 2006, Page(s):643 - 649
    Cited by:  Papers (111)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1876 KB) | HTML iconHTML

    In previous work on point matching, a set of points is often treated as an instance of a joint distribution to exploit global relationships in the point set. For nonrigid shapes, however, the local relationship among neighboring points is stronger and more stable than the global one. In this paper, we introduce the notion of a neighborhood structure for the general point matching problem. We formu... View full abstract»

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  • Adaptive support-weight approach for correspondence search

    Publication Year: 2006, Page(s):650 - 656
    Cited by:  Papers (463)  |  Patents (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1978 KB) | HTML iconHTML

    We present a new window-based method for correspondence search using varying support-weights. We adjust the support-weights of the pixels in a given support window based on color similarity and geometric proximity to reduce the image ambiguity. Our method outperforms other local methods on standard stereo benchmarks. View full abstract»

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  • A texture-based method for modeling the background and detecting moving objects

    Publication Year: 2006, Page(s):657 - 662
    Cited by:  Papers (495)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1499 KB) | HTML iconHTML

    This paper presents a novel and efficient texture-based method for modeling the background and detecting moving objects from a video sequence. Each pixel is modeled as a group of adaptive local binary pattern histograms that are calculated over a circular region around the pixel. The approach provides us with many advantages compared to the state-of-the-art. Experimental results clearly justify ou... View full abstract»

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  • Principal axis-based correspondence between multiple cameras for people tracking

    Publication Year: 2006, Page(s):663 - 671
    Cited by:  Papers (112)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1370 KB) | HTML iconHTML

    Visual surveillance using multiple cameras has attracted increasing interest in recent years. Correspondence between multiple cameras is one of the most important and basic problems which visual surveillance using multiple cameras brings. In this paper, we propose a simple and robust method, based on principal axes of people, to match people across multiple cameras. The correspondence likelihood r... View full abstract»

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  • IEEE Computer Society [advertisement]

    Publication Year: 2006, Page(s):672 - 6722
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  • TPAMI Information for authors

    Publication Year: 2006, Page(s):c3 - c33
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  • [Back cover]

    Publication Year: 2006, Page(s):c4 - c44
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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