کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1548928 | 997764 | 2009 | 8 صفحه PDF | دانلود رایگان |

Due to different shape modeling applications, partitioning a given complex 3D mesh model into some patches or meaningful subparts is one of the fundamental problems in digital geometry processing. By using the high-dimensional mean-shift clustering scheme in shape signature space, a new method is proposed which can generate user-specified segmentation results automatically for different applications. The shape signature is composed of mesh geometric attributes and its spectral harmonics. The latter one can reflect mesh frequency spectrum information. The low frequency components are essential for semantics-oriented segmentation, while the high frequency components are important for purely geometry-oriented segmentation. The effects of the proposed method are demonstrated by several examples.
Journal: Progress in Natural Science - Volume 19, Issue 4, 10 April 2009, Pages 471–478