Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
