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A Bayesian Decision for 3D Object Retrieval and Classification


Abdelalim Sadiq, Rachid Oulad Haj Thami


Vol. 6  No. 9  pp. 119-123


This paper presents a Bayesian-based method for classifying 3D objects into a set of pre-determined object classes. The basic idea is to determine a set of most similar three-dimensional objects. The three-dimensional models have to consider spatial properties such as shape. We use curvature as an intuitive and powerful similarity index for three-dimensional objects which consists of a histogram of the principal curvatures of each face of the mesh. An experimental evaluation demonstrates the satisfactory performance of our approach on a fifty three-dimensional models database.


3D Object, Bayesian classification, Curvature Index, 3D/3D indexing, 2D/3D Indexing