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    BMVC
    1998
    95views Computer Vision» more  BMVC 1998»
    Realisable Classifiers: Improving Operating Performance on Variable Cost Problems
    13 years 11 months ago
    Realisable Classifiers: Improving Operating Performance on Variable Cost Problems
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    A novel method is described for obtaining superior classification performance over a variable range of classification costs. By analysis of a set of existing classifiers using a r...
    Martin J. J. Scott, Mahesan Niranjan, Richard W. P...
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    BMVC
    1998
    174views Computer Vision» more  BMVC 1998»
    Choosing an Optimal Neural Network Size to aid a Search Through a Large Image Database
    13 years 11 months ago
    Choosing an Optimal Neural Network Size to aid a Search Through a Large Image Database
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    In this paper a fast method of selecting a neural network architecture for pattern recognition tasks is presented. We demonstrate that our proposed method of selecting both input ...
    Kieron Messer, Josef Kittler
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    BMVC
    1998
    186views Computer Vision» more  BMVC 1998»
    3D Trajectories from a Single Viewpoint using Shadows
    13 years 11 months ago
    3D Trajectories from a Single Viewpoint using Shadows
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    We consider the problem of obtaining the 3D trajectory of a ball from a sequence of images taken with a camera which is possibly rotating and zooming (but not translating). Techni...
    Ian D. Reid, A. North
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    BMVC
    1998
    246views Computer Vision» more  BMVC 1998»
    Reconstructing 3D Pose and Motion from a Single Camera View
    13 years 11 months ago
    Reconstructing 3D Pose and Motion from a Single Camera View
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    This paper presents a model based approach to human body tracking in which the 2D silhouette of a moving human and the corresponding 3D skeletal structure are encapsulated within ...
    Richard Bowden, T. A. Mitchell, Mansoor Sarhadi
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    BMVC
    1998
    199views Computer Vision» more  BMVC 1998»
    ORASSYLL: Object Recognition with Autonomously Learned and Sparse Symbolic Representations Based on Local Line Detectors
    13 years 11 months ago
    ORASSYLL: Object Recognition with Autonomously Learned and Sparse Symbolic Representations Based on Local Line Detectors
    Download  www.bmva.org
    We introduce an object recognition system in which objects are represented as a sparse and spatially organized set of local (bent) line segments. The line segments correspond to b...
    Norbert Krüger, Niklas Lüdtke
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