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Shape skeleton extraction is a fundamental pre-processing task in shape-based pattern recognition. This paper presents a new algorithm for fast and precise extraction of kinematic skeletons of 3D dynamic surface meshes. Unlike previous approaches, surface motions are characterized by the mesh edge-length deviation induced by its transformation through time. Then a static skeleton extraction algorithm based on Reeb graphs exploits this latter information to extract the kinematic skeleton. This hybrid static and dynamic shape analysis enables the precise detection of objectsÂ¿ articulations as well as shape topological transitions corresponding to possibly-articulated immobile objectsÂ¿ features. Experiments show that the proposed algorithm is faster than previous techniques and still achieves better accuracy.