Computer Science ›› 2015, Vol. 42 ›› Issue (5): 295-299.doi: 10.11896/j.issn.1002-137X.2015.05.060

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Segmentation of 3D Geometric Models Based on Mesh Laplace

YANG Jun, TIAN Zhen-hua, LI Long-jie and WANG Xiao-peng   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Segmentation is one of important methods and means to analyze shapes.A novel algorithm for segmentation of 3D geometric models was proposed based on mesh Laplace and k-means cluster aiming at the problem that the exis-ting mesh segmentation algorithms are sensitive to shape pose and time-consuming.Models are converted from spatial domain to spectral domain by using mesh Laplace in order to obtain the normalized forms,which are analyzed in spectral domain to avoid influence of variation of shape pose to segmentation results and greatly reduce the computing time.Experimental results show that the proposed algorithm is not only more efficient for generating correct and meaningful segmentations,but also more robust to variation of shape pose than existing algorithms.

Key words: Mesh segmentation,Mesh Laplace,k-means cluster,Spectral embeding,Robustness

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