Titlebook: Human Motion; Understanding, Model Bodo Rosenhahn,Reinhard Klette,Dimitris Metaxas Book 2008 Springer Science+Business Media B.V. 2008 3D.P

人工制品

Markerless Motion Capture for Biomechanical Applications markerless motion capture is critical. The implementation of this new methodology offers the promise for simple, timeefficient, and potentially more meaningful assessments of human movement in research and clinical practice.

疾驰

Contours, Optic Flow, and Prior Knowledge: Cues for Capturing 3D Human Motion in Videosbackground. The optic flow computed between two successive frames is used for pose prediction. It improves the quality of tracking in case of fast motion and/or low frame rates. In order to cope with unreliable or insufficient data, the framework is further extended by the use of prior knowledge on static joint angle configurations.

intertwine

Motion Capture for Interaction Environmentslable in real-time. Because speed is an issue, different optimization methods are compared, namely Gauss-Newton(Levenberg-Marquardt), Gradient Descent, and Stochastic Meta Descent. Experiments on human movement show the advantages and disadvantages of each method.

Gratuitous

枫树

懒惰民族

https://doi.org/10.1007/978-1-4020-6693-13D; Performance; animation; biomechanics; computer graphics; modeling; rendering; robotics

Cognizance

伪善

PAEAN

Topologically Constrained Isometric Embeddingc geometry of manifolds with complicated topology. Since our algorithm matches nonlocal structures, it is robust even to strong noise. We show experimental results on both synthetic and real data demonstrating the advantages of our approach over stateof- the-art manifold learning methods.

胰脏