Statistical methods descriptor matching par collier olivier (9 résultats)

Etat : New.

Etat : New. pp. 128.

paperback. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Etat : Neu. Statistical Methods for Descriptor Matching | Mathematical Problems in Computer Vision | Olivier Collier | Taschenbuch | Englisch | 2014 | Scholars' Press | EAN 9783639715392 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Taschenbuch. Etat : 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.…

Etat : New. Print on Demand pp. 128 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Etat : New. PRINT ON DEMAND pp. 128.

Taschenbuch. Etat : 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.…

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. 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.OmniScriptum SRL, Str. Armeneasca 28/1, office 1, 2012 Chisinau 128 pp. Englisch.…