Abstract

In this paper, we propose a novel mesh-decomposition scheme called salience-guided mesh decomposition. The concept of salience, which originated in cognitive psychology, asserts that the salience of a part can be determined by (at least) three factors: the protrusion, the boundary strength, and the relative size of the part. We try to convert these conceptual rules into real computational processes, and use them to guide a three-dimensional (3D) mesh decomposition process in such a way that the significant components can be precisely identified and efficiently extracted from a given 3D mesh. The proposed decomposition scheme not only identifies the parts' boundaries defined by the minima rule, but also labels each part with a quantitative degree of visual salience during the mesh decomposition process. The experimental results show that the proposed scheme is indeed effective and powerful in decomposing a 3D mesh into its significant components

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