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Pattern Analysis and Machine Intelligence, IEEE Transactions on

Issue 11 • Date Nov. 2009

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

    Publication Year: 2009 , Page(s): c1
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  • [Inside front cover]

    Publication Year: 2009 , Page(s): c2
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  • Bidirectional Texture Function Modeling: A State of the Art Survey

    Publication Year: 2009 , Page(s): 1921 - 1940
    Cited by:  Papers (13)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (5131 KB) |  | HTML iconHTML  

    An ever-growing number of real-world computer vision applications require classification, segmentation, retrieval, or realistic rendering of genuine materials. However, the appearance of real materials dramatically changes with illumination and viewing variations. Thus, the only reliable representation of material visual properties requires capturing of its reflectance in as wide range of light an... View full abstract»

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  • Discriminative Face Alignment

    Publication Year: 2009 , Page(s): 1941 - 1954
    Cited by:  Papers (17)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2941 KB) |  | HTML iconHTML  

    This paper proposes a discriminative framework for efficiently aligning images. Although conventional Active Appearance Models (AAMs)-based approaches have achieved some success, they suffer from the generalization problem, i.e., how to align any image with a generic model. We treat the iterative image alignment problem as a process of maximizing the score of a trained two-class classifier that is... View full abstract»

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  • Face Photo-Sketch Synthesis and Recognition

    Publication Year: 2009 , Page(s): 1955 - 1967
    Cited by:  Papers (74)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (3867 KB) |  | HTML iconHTML  

    In this paper, we propose a novel face photo-sketch synthesis and recognition method using a multiscale Markov Random Fields (MRF) model. Our system has three components: 1) given a face photo, synthesizing a sketch drawing; 2) given a face sketch drawing, synthesizing a photo; and 3) searching for face photos in the database based on a query sketch drawn by an artist. It has useful applications f... View full abstract»

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  • Face Relighting from a Single Image under Arbitrary Unknown Lighting Conditions

    Publication Year: 2009 , Page(s): 1968 - 1984
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (3363 KB) |  | HTML iconHTML  

    In this paper, we present a new method to modify the appearance of a face image by manipulating the illumination condition, when the face geometry and albedo information is unknown. This problem is particularly difficult when there is only a single image of the subject available. Recent research demonstrates that the set of images of a convex Lambertian object obtained under a wide variety of ligh... View full abstract»

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  • Rotation Invariant Kernels and Their Application to Shape Analysis

    Publication Year: 2009 , Page(s): 1985 - 1999
    Cited by:  Papers (11)
    Multimedia
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1907 KB) |  | HTML iconHTML  

    Shape analysis requires invariance under translation, scale, and rotation. Translation and scale invariance can be realized by normalizing shape vectors with respect to their mean and norm. This maps the shape feature vectors onto the surface of a hypersphere. After normalization, the shape vectors can be made rotational invariant by modeling the resulting data using complex scalar-rotation invari... View full abstract»

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  • SemiBoost: Boosting for Semi-Supervised Learning

    Publication Year: 2009 , Page(s): 2000 - 2014
    Cited by:  Papers (63)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (4238 KB) |  | HTML iconHTML  

    Semi-supervised learning has attracted a significant amount of attention in pattern recognition and machine learning. Most previous studies have focused on designing special algorithms to effectively exploit the unlabeled data in conjunction with labeled data. Our goal is to improve the classification accuracy of any given supervised learning algorithm by using the available unlabeled examples. We... View full abstract»

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  • Signature Detection and Matching for Document Image Retrieval

    Publication Year: 2009 , Page(s): 2015 - 2031
    Cited by:  Papers (20)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (5318 KB) |  | HTML iconHTML  

    As one of the most pervasive methods of individual identification and document authentication, signatures present convincing evidence and provide an important form of indexing for effective document image processing and retrieval in a broad range of applications. However, detection and segmentation of free-form objects such as signatures from clustered background is currently an open document anal... View full abstract»

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  • A Statistical Approach to Material Classification Using Image Patch Exemplars

    Publication Year: 2009 , Page(s): 2032 - 2047
    Cited by:  Papers (128)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (3693 KB) |  | HTML iconHTML  

    In this paper, we investigate material classification from single images obtained under unknown viewpoint and illumination. It is demonstrated that materials can be classified using the joint distribution of intensity values over extremely compact neighborhoods (starting from as small as 3times3 pixels square) and that this can outperform classification using filter banks with large support. It is... View full abstract»

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  • Bregman Divergences and Surrogates for Learning

    Publication Year: 2009 , Page(s): 2048 - 2059
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1375 KB) |  | HTML iconHTML  

    Bartlett et al. (2006) recently proved that a ground condition for surrogates, classification calibration, ties up their consistent minimization to that of the classification risk, and left as an important problem the algorithmic questions about their minimization. In this paper, we address this problem for a wide set which lies at the intersection of classification calibrated surrogates and those... View full abstract»

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  • A New Algorithm and System for the Characterization of Handwriting Strokes with Delta-Lognormal Parameters

    Publication Year: 2009 , Page(s): 2060 - 2072
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2539 KB) |  | HTML iconHTML  

    In this paper, we present a new analytical method for estimating the parameters of delta-lognormal functions and characterizing handwriting strokes. According to the kinematic theory of rapid human movements, these parameters contain information on both the motor commands and the timing properties of a neuromuscular system. The new algorithm, called XZERO, exploits relationships between the zero c... View full abstract»

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  • Optimal Decision Rule with Class-Selective Rejection and Performance Constraints

    Publication Year: 2009 , Page(s): 2073 - 2082
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (896 KB) |  | HTML iconHTML  

    The problem of defining a decision rule which takes into account performance constraints and class-selective rejection is formalized in a general framework. In the proposed formulation, the problem is defined using three kinds of criteria. The first is the cost to be minimized, which defines the objective function, the second are the decision options, determined by the admissible assignment classe... View full abstract»

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  • Optimal Combination of Nested Clusters by a Greedy Approximation Algorithm

    Publication Year: 2009 , Page(s): 2083 - 2087
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (367 KB) |  | HTML iconHTML  

    Given a set of clusters, we consider an optimization problem which seeks a subset of clusters that maximizes the microaverage F-measure. This optimal value can be used as an evaluation measure of the goodness of clustering. For arbitrarily overlapping clusters, finding the optimal value is NP-hard. We claim that a greedy approximation algorithm yields the global optimal solution for clusters that ... View full abstract»

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  • A Small Sphere and Large Margin Approach for Novelty Detection Using Training Data with Outliers

    Publication Year: 2009 , Page(s): 2088 - 2092
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (724 KB) |  | HTML iconHTML  

    We present a small sphere and large margin approach for novelty detection problems, where the majority of training data are normal examples. In addition, the training data also contain a small number of abnormal examples or outliers. The basic idea is to construct a hypersphere that contains most of the normal examples, such that the volume of this sphere is as small as possible, while at the same... View full abstract»

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  • FINE: Fisher Information Nonparametric Embedding

    Publication Year: 2009 , Page(s): 2093 - 2098
    Cited by:  Papers (18)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (915 KB) |  | HTML iconHTML  

    We consider the problems of clustering, classification, and visualization of high-dimensional data when no straightforward Euclidean representation exists. In this paper, we propose using the properties of information geometry and statistical manifolds in order to define similarities between data sets using the Fisher information distance. We will show that this metric can be approximated using en... View full abstract»

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  • Tailored Aggregation for Classification

    Publication Year: 2009 , Page(s): 2098 - 2105
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (984 KB) |  | HTML iconHTML  

    Compression and variable selection are two classical strategies to deal with large-dimension data sets in classification. We propose an alternative strategy, called aggregation, which consists of a clustering step of redundant variables and a compression step within each group. We develop a statistical framework to define tailored aggregation methods that can be combined with selection methods to ... View full abstract»

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  • Toward Practical Smile Detection

    Publication Year: 2009 , Page(s): 2106 - 2111
    Cited by:  Papers (55)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (870 KB) |  | HTML iconHTML  

    Machine learning approaches have produced some of the highest reported performances for facial expression recognition. However, to date, nearly all automatic facial expression recognition research has focused on optimizing performance on a few databases that were collected under controlled lighting conditions on a relatively small number of subjects. This paper explores whether current machine lea... View full abstract»

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  • iccp10: Call for Papers

    Publication Year: 2009 , Page(s): 2112
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    Freely Available from IEEE
  • TPAMI Information for authors

    Publication Year: 2009 , Page(s): c3
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    Freely Available from IEEE
  • [Back cover]

    Publication Year: 2009 , Page(s): c4
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    Freely Available from IEEE

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