Similarity estimation of 3D shapes using modal strain energy

Shape comparison between 3D models is essential for shape recognition, retrieval, classification, etc. In this paper, we propose a method for comparing 3D shapes, which is invariant under translation, rotation and scaling of models and is robust to non-uniformly distributed and incomplete data sets. A modal model is constructed from input data using vibration modes and then shape similarity is evaluated with modal strain energy. The proposed method provides global-to-local ordering of shape deformation using vibration modes ordered by frequency. Thus, we evaluated similarity in terms of global properties of shape without being affected localized shape features using ordered shape representation and modal strain energy.