marker free human motion capture di grest daniel (6 risultati)

Taschenbuch. Condizione: 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: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Taschenbuch. Condizione: Neu. 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 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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 176 pp. Englisch.

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Taschenbuch. Condizione: 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 to 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.

Condizione: 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 University Copenhagen. His research.

Taschenbuch. Condizione: 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 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.