Marker-Free Human Motion Capture: Estimation Concepts and Possibilities with Computer Vision Techniques from a Single Camera View Point

 
9783838382227: Marker-Free Human Motion Capture: Estimation Concepts and Possibilities with Computer Vision Techniques from a Single Camera View Point
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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.

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Dr.-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 field is Computer Vision and Graphics, especially motion and model reconstruction with non-linear optimization methods.

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Book Description Condition: New. Publisher/Verlag: LAP Lambert Academic Publishing | Estimation Concepts and Possibilities with Computer Vision Techniques from a Single Camera View Point | 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. | Format: Paperback | Language/Sprache: english | 252 gr | 176 pp. Seller Inventory # K9783838382227

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Book Description LAP Lambert Acad. Publ. Jul 2010, 2010. Taschenbuch. Condition: 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. 176 pp. Englisch. Seller Inventory # 9783838382227

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Book Description LAP Lambert Acad. Publ. Jul 2010, 2010. Taschenbuch. Condition: 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. 176 pp. Englisch. Seller Inventory # 9783838382227

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Book Description LAP Lambert Acad. Publ. Jul 2010, 2010. Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand 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. Seller Inventory # 9783838382227

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Book Description LAP Lambert Academic Publishing. Paperback. Condition: New. 176 pages. Dimensions: 8.7in. x 5.9in. x 0.4in.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. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Paperback. Seller Inventory # 9783838382227

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Book Description LAP Lambert Academic Publishing, Germany, 2010. Paperback. Condition: New. Language: English. Brand new Book. 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. Seller Inventory # KNV9783838382227

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