Titlebook: Computer Vision - ECCV 2004; 8th European Confere Tomás Pajdla,Jiří Matas Conference proceedings 2004 Springer-Verlag Berlin Heidelberg 200

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Support Blob Machinese loss function introduced in support vector regression [22], we use a quadratic .-insensitive loss function instead of the original quadratic measure. The .-insensitivity loss allows errors in the approximating function without actual increase in loss. It penalizes errors only when they become larg

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Detecting Keypoints with Stable Position, Orientation, and Scale under Illumination Changesd on extending the Förstner-Harris approach to general motion models and robust template matching. We also incorporate a simple local appearance model to ensure good resistance to the most common illumination variations. We illustrate the resulting methods and quantify their performance on test imag

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Computer Vision - ECCV 2004978-3-540-24673-2Series ISSN 0302-9743 Series E-ISSN 1611-3349