Unsupervised co-segmentation for 3D shapes using iterative multi-label optimization
This paper presents an unsupervised algorithm for co-segmentation of a set of 3D shapes of the same family. Taking the over-segmentation results as input, our approach clusters the primitive patches to generate an initial guess. Then, it iteratively builds a statistical model to describe each cluste...
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Main Authors: | , , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2013
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/105015 http://hdl.handle.net/10220/16822 |
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Institution: | Nanyang Technological University |
Language: | English |
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