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Synopsis
Many applications, as in computer vision or medicine, aim at identifying the similarities between several images or signals. Thereafter, it is possible to detect objects, to follow them, or to overlap different pictures. In every case, the algorithmic procedures that treat the images use a selection of keypoints that they try to match by pairs. The most popular algorithm nowadays is SIFT, that performs keypoint selection, descriptor calculation, and provides a criterion for global descriptor matching. We considered changing the classical descriptor, which resulted in a shift testing problem that we solved in the minimax frame. Then, we gave a rigorous statistical formulation for the global descriptor matching problem and studied it in some special cases.
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About the Author
Olivier Collier is a former student of the Ecole Normale Supérieure de Cachan. He obtained his PhD under the supervision of Arnak Dalalyan at Université Paris-Est (France). He is now a postdoctoral researcher at Ecole des Mines de Paris and Institut Curie.
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Statistical Methods for Descriptor Matching
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Scholars' Press Apr 2014, 2014
ISBN 10: 363971539X
ISBN 13: 9783639715392
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Many applications, as in computer vision or medicine, aim at identifying the similarities between several images or signals. Thereafter, it is possible to detect objects, to follow them, or to overlap different pictures. In every case, the algorithmic procedures that treat the images use a selection of keypoints that they try to match by pairs. The most popular algorithm nowadays is SIFT, that performs keypoint selection, descriptor calculation, and provides a criterion for global descriptor matching. We considered changing the classical descriptor, which resulted in a shift testing problem that we solved in the minimax frame. Then, we gave a rigorous statistical formulation for the global descriptor matching problem and studied it in some special cases. 128 pp. Englisch. Seller Inventory # 9783639715392
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Statistical Methods for Descriptor Matching
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Statistical Methods for Descriptor Matching : Mathematical Problems in Computer Vision
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Many applications, as in computer vision or medicine, aim at identifying the similarities between several images or signals. Thereafter, it is possible to detect objects, to follow them, or to overlap different pictures. In every case, the algorithmic procedures that treat the images use a selection of keypoints that they try to match by pairs. The most popular algorithm nowadays is SIFT, that performs keypoint selection, descriptor calculation, and provides a criterion for global descriptor matching. We considered changing the classical descriptor, which resulted in a shift testing problem that we solved in the minimax frame. Then, we gave a rigorous statistical formulation for the global descriptor matching problem and studied it in some special cases. Seller Inventory # 9783639715392
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Statistical Methods for Descriptor Matching
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Statistical Methods for Descriptor Matching
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Statistical Methods for Descriptor Matching
Published by
Scholars' Press Apr 2014, 2014
ISBN 10: 363971539X
ISBN 13: 9783639715392
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Taschenbuch. Condition: Neu. Neuware -Many applications, as in computer vision or medicine, aim at identifying the similarities between several images or signals. Thereafter, it is possible to detect objects, to follow them, or to overlap different pictures. In every case, the algorithmic procedures that treat the images use a selection of keypoints that they try to match by pairs. The most popular algorithm nowadays is SIFT, that performs keypoint selection, descriptor calculation, and provides a criterion for global descriptor matching. We considered changing the classical descriptor, which resulted in a shift testing problem that we solved in the minimax frame. Then, we gave a rigorous statistical formulation for the global descriptor matching problem and studied it in some special cases.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 128 pp. Englisch. Seller Inventory # 9783639715392
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Statistical Methods for Descriptor Matching
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VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2014
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Statistical Methods for Descriptor Matching: Mathematical Problems in Computer Vision
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