Shape skeleton extraction is a fundamental preprocessing 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 local 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 objects' articulations as well as potentially-articulated immobile shape features. Experiments show that the proposed algorithm is faster than previous techniques and still achieves better accuracy.