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Pattern Recognition (ICPR), 2010 20th International Conference on

Date 23-26 Aug. 2010

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Displaying Results 1 - 25 of 1156
  • [Front cover]

    Publication Year: 2010, Page(s): C1
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  • [Title page i]

    Publication Year: 2010, Page(s): i
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  • [Title page iii]

    Publication Year: 2010, Page(s): iii
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  • [Copyright notice]

    Publication Year: 2010, Page(s): iv
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  • Table of contents

    Publication Year: 2010, Page(s):v - lxxvii
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  • Message from General Chair

    Publication Year: 2010, Page(s):lxxviii - lxxix
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  • Message from Technical Program Chairs

    Publication Year: 2010, Page(s): lxxx
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  • Organizing Committee

    Publication Year: 2010, Page(s):lxxxi - lxxxii
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  • ICPR 2010 Track Co-chairs

    Publication Year: 2010, Page(s):lxxxiii - lxxxiv
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  • Reviewers

    Publication Year: 2010, Page(s):lxxxv - xci
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  • Minimizing Geometric Distance by Iterative Linear Optimization

    Publication Year: 2010, Page(s):1 - 4
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (500 KB) | HTML iconHTML

    This paper proposes an algorithm that solves planar homography by iterative linear optimization. We iteratively employ direct linear transformation (DLT) algorithm to robustly estimate the homography induced by a given set of point correspondences under perspective transformation. By simple on-the-fly homogeneous coordinate adjustment we progressively minimize the difference between the algebraic ... View full abstract»

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  • Hyper Least Squares and Its Applications

    Publication Year: 2010, Page(s):5 - 8
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (518 KB) | HTML iconHTML

    We present a new form of least squares (LS), called "hyper LS", for geometric problems that frequently appear in computer vision applications. Doing rigorous error analysis, we maximize the accuracy by introducing a normalization that eliminates statistical bias up to second order noise terms. Our method yields a solution comparable to maximum likelihood (ML) without iterations, even in large nois... View full abstract»

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  • Integrating a Discrete Motion Model into GMM Based Background Subtraction

    Publication Year: 2010, Page(s):9 - 12
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (604 KB) | HTML iconHTML

    GMM based algorithms have become the de facto standard for background subtraction in video sequences, mainly because of their ability to track multiple background distributions, which allows them to handle complex scenes including moving trees, flags moving in the wind etc. However, it is not always easy to determine which distributions of the mixture belong to the background and which distributio... View full abstract»

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  • Saliency Based on Multi-scale Ratio of Dissimilarity

    Publication Year: 2010, Page(s):13 - 16
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (670 KB) | HTML iconHTML

    Recently, many vision applications tend to utilize saliency maps derived from input images to guide them to focus on processing salient regions in images. In this paper, we propose a simple and effective method to quantify the saliency for each pixel in images. Specially, we define the saliency for a pixel in a ratio form, where the numerator measures the number of dissimilar pixels in its center-... View full abstract»

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  • Online Principal Background Selection for Video Synopsis

    Publication Year: 2010, Page(s):17 - 20
    Cited by:  Papers (3)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (556 KB) | HTML iconHTML

    Video synopsis provides a means for fast browsing of activities in video. Principal background selection (PBS) is an important step in video synopsis. Existing methods make PBS in an offline way and at a high memory cost. In this paper we propose a novel background selection method, ``online principal background selection'' (OPBS). The OPBS selects n principal backgrounds from N backgrounds in an ... View full abstract»

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  • Large Margin Classifier Based on Affine Hulls

    Publication Year: 2010, Page(s):21 - 24
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (470 KB) | HTML iconHTML

    This paper introduces a geometrically inspired large-margin classifier that can be a better alternative to the Support Vector Machines (SVMs) for the classification problems with limited number of training samples. In contrast to the SVM classifier, we approximate classes with affine hulls of their class samples rather than convex hulls, which may be unrealistically tight in high-dimensional space... View full abstract»

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  • 2D Shape Recognition Using Information Theoretic Kernels

    Publication Year: 2010, Page(s):25 - 28
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (798 KB) | HTML iconHTML

    In this paper, a novel approach for contour based 2D shape recognition is proposed, using a class of information theoretic kernels recently introduced. This kind of kernels, based on a non-extensive generalization of the classical Shannon information theory, are defined on probability measures. In the proposed approach, chain code representations are first extracted from the contours; then n-gram ... View full abstract»

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  • Time Series Classification Using Support Vector Machine with Gaussian Elastic Metric Kernel

    Publication Year: 2010, Page(s):29 - 32
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (507 KB) | HTML iconHTML

    Motivated by the great success of dynamic time warping (DTW) in time series matching, Gaussian DTW kernel had been developed for support vector machine (SVM)-based time series classification. Counter-examples, however, had been subsequently reported that Gaussian DTW kernel usually cannot outperform Gaussian RBF kernel in the SVM framework. In this paper, by extending the Gaussian RBF kernel, we p... View full abstract»

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  • Multiplicative Update Rules for Multilinear Support Tensor Machines

    Publication Year: 2010, Page(s):33 - 36
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (624 KB) | HTML iconHTML

    In this paper, we formulate the Multilinear Support Tensor Machines (MSTMs) problem in a similar to the Non-negative Matrix Factorization (NMF) algorithm way. A novel set of simple and robust multiplicative update rules are proposed in order to find the multilinear classifier. Updates rules are provided for both hard and soft margin MSTMs and the existence of a bias term is also investigated. We p... View full abstract»

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  • Support Vectors Selection for Supervised Learning Using an Ensemble Approach

    Publication Year: 2010, Page(s):37 - 40
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (565 KB) | HTML iconHTML

    Support Vector Machines (SVMs) are popular for pattern classification. However, training a SVM requires large memory and high processing time, especially for large datasets, which limits their applications. To speed up their training, we present a new efficient support vector selection method based on ensemble margin, a key concept in ensemble classifiers. This algorithm exploits a new version of ... View full abstract»

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  • Estimating Apparent Motion on Satellite Acquisitions with a Physical Dynamic Model

    Publication Year: 2010, Page(s):41 - 44
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3846 KB) | HTML iconHTML

    The paper presents a motion estimation method based on data assimilation in a dynamic model, named Image Model, expressing the physical evolution of a quantity observed on the images. The application concerns the retrieval of apparent surface velocity from a sequence of satellite data, acquired over the ocean. The Image Model includes a shallow-water approximation for the dynamics of the velocity ... View full abstract»

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  • Multiple View Geometries for Mirrors and Cameras

    Publication Year: 2010, Page(s):45 - 48
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (623 KB) | HTML iconHTML

    In this paper, we analyze the multiple view geometry for a camera and mirrors, and propose a method for computing the geometry of the camera and mirrors accurately from fewer corresponding points than the existing methods. The geometry between a camera and mirrors can be described as the multiple view geometry for a real camera and virtual cameras. We show that very strong constraints on geometrie... View full abstract»

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  • Perspective Reconstruction and Camera Auto-Calibration as Rectangular Polynomial Eigenvalue Problem

    Publication Year: 2010, Page(s):49 - 52
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1460 KB) | HTML iconHTML

    Motion-based 3D reconstruction (SfM) with missing data has been a challenging computer vision task since the late 90s. Under perspective camera model, one of the most difficult problems is camera auto-calibration which means determining the intrinsic camera parameters without using any known calibration object or assuming special properties of the scene. This paper presents a novel algorithm to pe... View full abstract»

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  • Multi-camera Platform Calibration Using Multi-linear Constraints

    Publication Year: 2010, Page(s):53 - 56
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1407 KB) | HTML iconHTML

    We present a novel calibration method for multi-camera platforms, based on multi-linear constraints. The calibration method can recover the relative orientation between the different cameras on the platform, even when there are no corresponding feature points between the cameras, i.e. there are no overlaps between the cameras. It is shown that two translational motions in different directions are ... View full abstract»

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  • A Game-Theoretic Approach to Robust Selection of Multi-view Point Correspondence

    Publication Year: 2010, Page(s):57 - 60
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1693 KB) | HTML iconHTML

    In this paper we introduce a robust matching technique that allows very accurate selection of corresponding feature points from multiple views. Robustness is achieved by enforcing global geometric consistency at an early stage of the matching process, without the need of subsequent verification through reprojection. The global consistency is reduced to a pairwise compatibility making use of the si... View full abstract»

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