三凸量-华东师范大学学报.pdfVIP

6 ( ) No. 6 2017 11 Journal of East China Normal University (Natural Science) Nov. 2017 : 1000-5641(2017)06-0063-13 , , , ( , 200062) : , , , . (Principal Component Analysis, PCA) , , , , , . , , . : ; ; : TP391.4 : A DOI: 10.3969/j.issn.1000-5641.2017.06.006 An improved convexity measure for 3D meshes LI Rui, LIU Lei, SHENG Yun, ZHANG Gui-xu (School of Computer Science and Software Engineering, East China Normal University, Shanghai 200062, China) Abstract: In this paper we proposed an improved 3D mesh convexity measure by projecting only once a given 3D mesh onto the orthogonal 2D planes along its principal directions. Unlike the previous work which was time-consuming and required constant adaptations of the projection direction, we used the calculated result along the principal directions as an initial estimate of mesh convexity, followed by a correction process. In the initial estimation, our measure computed only once the summed area ratio of mesh silhouette images to mesh faces, along the principal directions of the mesh. Then, the mesh was sliced into a number of 2D cross sections along its principal directions. Finally, a 2D convexity measure for the 2D sliced cross sections was employed to correct the convexity overestimated by the initial estimation. Experimental results had demonstrated the effectiveness and effciency of the improved convexity measure against the existing ones. Key words: shape analysis; convexity measure; prin