In this paper, we propose to address the semantic- oriented 3D mesh hierarchical segmentation problem, using enhanced topological skeletons. This high level information drives both the feature boundary computation as well as the feature hierarchy definition. Proposed hierarchical scheme is based on the key idea that the topology of a feature is a more important decomposition criterion than its geometry. First, the enhanced topological skeleton of the input triangulated surface is constructed. Then it is used to delimit the core of the object and to identify junction areas. This second step results in a fine segmentation of the object. Finally, a fine to coarse strategy enables a semantic-oriented hierarchical composition of features, subdividing human limbs into arms and hands for example. Method performance is evaluated according to seven criteria enumerated in latest segmentation surveys. Thanks to the high level description it uses as an input, presented approach results, with low computation times, in robust and meaningful compatible hierarchical decompositions.