Grest daniel (6 résultats)
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Taschenbuch. Etat : Neu. Marker-Free Human Motion Capture | Estimation Concepts and Possibilities with Computer Vision Techniques from a Single Camera View Point | Daniel Grest | Taschenbuch | 176 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838382227 | Verantwortliche Person für die EU: preigu GmbH & Co. KG,… Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Vendeur : Mispah books, Redhill, SURRE, Royaume-UniMispah books
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Paperback. Etat : Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AllemagneBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Human Motion Capture is a widely used technique to obtain motion data for animation of virtual characters. Commercial optical motion capture systems are marker-based. This book is about marker-free motion capture and its possibilities t…o acquire motion from a single viewing direction. The focus of this book is on the optimization framework, which can be applied to every pose estimation problem of articulated objects. The motion function is formed with a combination of kinematic chains. This formulation leads to a Nonlinear Optimization problem and is solved with gradient-based methods, which are compared with respect to their efficiency. A new contribution is the inclusion of second order motion derivatives within the pose estimation. The pose estimation step requires correspondences between known model of the person and observed data. Computer Vision techniques are used to combine multiple types of correspondences, which are used simultaneously in the estimation without making approximations to the motion or optimization function, namely 3D-3D correspondences from stereo algorithms and 3D-2D correspondences from image silhouettes and 2D point tracking. 176 pp. Englisch.
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Grest DanielDr.-Ing. Grest obtained his Master degree in Computer Science Engineering and his PhD at the Multimedia Image Processing Group in Kiel, Germany. He is currently Professor at the Aalborg Universi…ty Copenhagen. His research.
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Human Motion Capture is a widely used technique to obtain motion data for animation of virtual characters. Commercial optical motion capture systems are marker-based. This book is about marker-free motion capture and its possibilities to ac…quire motion from a single viewing direction. The focus of this book is on the optimization framework, which can be applied to every pose estimation problem of articulated objects. The motion function is formed with a combination of kinematic chains. This formulation leads to a Nonlinear Optimization problem and is solved with gradient-based methods, which are compared with respect to their efficiency. A new contribution is the inclusion of second order motion derivatives within the pose estimation. The pose estimation step requires correspondences between known model of the person and observed data. Computer Vision techniques are used to combine multiple types of correspondences, which are used simultaneously in the estimation without making approximations to the motion or optimization function, namely 3D-3D correspondences from stereo algorithms and 3D-2D correspondences from image silhouettes and 2D point tracking.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 176 pp. Englisch.
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Vendeur : AHA-BUCH GmbH, Einbeck, AllemagneAHA-BUCH GmbH
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Human Motion Capture is a widely used technique to obtain motion data for animation of virtual characters. Commercial optical motion capture systems are marker-based. This book is about marker-free motion capture and its possibilities to acq…uire motion from a single viewing direction. The focus of this book is on the optimization framework, which can be applied to every pose estimation problem of articulated objects. The motion function is formed with a combination of kinematic chains. This formulation leads to a Nonlinear Optimization problem and is solved with gradient-based methods, which are compared with respect to their efficiency. A new contribution is the inclusion of second order motion derivatives within the pose estimation. The pose estimation step requires correspondences between known model of the person and observed data. Computer Vision techniques are used to combine multiple types of correspondences, which are used simultaneously in the estimation without making approximations to the motion or optimization function, namely 3D-3D correspondences from stereo algorithms and 3D-2D correspondences from image silhouettes and 2D point tracking.
