jun sik kim (11 risultati)

Condizione: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Condizione: New. pp. 196.

Taschenbuch. Condizione: Neu. Metric Invariants for Camera Calibration | Designing algorithms from algebraic rank analysis | Jun-Sik Kim (u. a.) | Taschenbuch | 196 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846509883 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Couverture souple. Condizione: Très bon. Condizione sovraccoperta: Très bon. Republic of Korea, The Instituteof Korean Independence Movement Studies, 2014, soft cover with DJ, about 9 X 7 inches, 319 pages, illustrated in B&W and in color. Books is near mint except for a few minor bumps to sopme corners. Interior is as new.WARNING : additional postage will apply for shipping out of North America. Please ask me before command.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Reconstructing a metric structure of a scene from images has been one of the important topics in computer vision. In this book, we focus on a simple diagonal rank-deficient form of a 2D metric invariant, a conic dual to the circular points. By manipulating image features to constrain the simple form algebraically, the metric reconstruction can be achieved. We start from second order curves such as concentric circles or confocal conics to be used as basic features. By simply subtracting them, affine and metric properties of a plane are recovered. The geometric meanings of the resulting subtraction matrices are also investigated. The idea of algebraically manipulating features extend to an ``addition method'' using human recognizable features such as a rectangle. Its parallelism and orthogonality enables us to obtain information of the scene structure. As a generalization, we propose a framework to unify the geometric constraints used in camera calibration and in metric reconstruction. We show that scene constraints can be converted into constraints of cameras, and that a flexible algorithm to metric-reconstruct scenes from images can be developed in the proposed unified framework. 196 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kim Jun-SikJun-Sik KIM: Ph.D. in Electrical Engineering (2006) from KAIST, South Korea Project Scientist at the Robotics Institute, Carnegie Mellon University, USA. In So KWEON: Ph.D. in Robotics (1990) from Carnegie Mellon Univers.

Condizione: New. Print on Demand pp. 196 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Condizione: New. PRINT ON DEMAND pp. 196.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Reconstructing a metric structure of a scene from images has been one of the important topics in computer vision. In this book, we focus on a simple diagonal rank-deficient form of a 2D metric invariant, a conic dual to the circular points. By manipulating image features to constrain the simple form algebraically, the metric reconstruction can be achieved. We start from second order curves such as concentric circles or confocal conics to be used as basic features. By simply subtracting them, affine and metric properties of a plane are recovered. The geometric meanings of the resulting subtraction matrices are also investigated. The idea of algebraically manipulating features extend to an ``addition method'' using human recognizable features such as a rectangle. Its parallelism and orthogonality enables us to obtain information of the scene structure. As a generalization, we propose a framework to unify the geometric constraints used in camera calibration and in metric reconstruction. We show that scene constraints can be converted into constraints of cameras, and that a flexible algorithm to metric-reconstruct scenes from images can be developed in the proposed unified framework.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 196 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Reconstructing a metric structure of a scene from images has been one of the important topics in computer vision. In this book, we focus on a simple diagonal rank-deficient form of a 2D metric invariant, a conic dual to the circular points. By manipulating image features to constrain the simple form algebraically, the metric reconstruction can be achieved. We start from second order curves such as concentric circles or confocal conics to be used as basic features. By simply subtracting them, affine and metric properties of a plane are recovered. The geometric meanings of the resulting subtraction matrices are also investigated. The idea of algebraically manipulating features extend to an ``addition method'' using human recognizable features such as a rectangle. Its parallelism and orthogonality enables us to obtain information of the scene structure. As a generalization, we propose a framework to unify the geometric constraints used in camera calibration and in metric reconstruction. We show that scene constraints can be converted into constraints of cameras, and that a flexible algorithm to metric-reconstruct scenes from images can be developed in the proposed unified framework.