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- Publisher Website: 10.1109/TVCG.2020.3032566
- PMID: 33079671
- WOS: WOS:000790817100014
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Article: SEG-MAT: 3D Shape Segmentation Using Medial Axis Transform
Title | SEG-MAT: 3D Shape Segmentation Using Medial Axis Transform |
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Authors | |
Keywords | Shape Analysis Shape Segmentation Medial Axis Transform Geometry |
Issue Date | 2020 |
Publisher | Institute of Electrical and Electronics Engineers. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=2945 |
Citation | IEEE Transactions on Visualization and Computer Graphics, 2020, Epub 2020-10-20 How to Cite? |
Abstract | Segmenting arbitrary 3D objects into constituent parts that are structurally meaningful is a fundamental problem encountered in a wide range of computer graphics applications. Existing methods for 3D shape segmentation suffer from complex geometry processing and heavy computation caused by using low-level features and fragmented segmentation results due to the lack of global consideration. We present an efficient method, called SEG-MAT, based on the medial axis transform (MAT) of the input shape. Specifically, with the rich geometrical and structural information encoded in the MAT, we are able to develop a simple and principled approach to effectively identify the various types of junctions between different parts of a 3D shape. Extensive evaluations and comparisons show that our method outperforms the state-of-the-art methods in terms of segmentation quality and is also one order of magnitude faster |
Persistent Identifier | http://hdl.handle.net/10722/293191 |
ISSN | 2023 Impact Factor: 4.7 2023 SCImago Journal Rankings: 2.056 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | LIN, C | - |
dc.contributor.author | LIU, L | - |
dc.contributor.author | LI, C | - |
dc.contributor.author | Kobbelt, L | - |
dc.contributor.author | Wang, B | - |
dc.contributor.author | Xin, S | - |
dc.contributor.author | Wang, W | - |
dc.date.accessioned | 2020-11-23T08:13:08Z | - |
dc.date.available | 2020-11-23T08:13:08Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | IEEE Transactions on Visualization and Computer Graphics, 2020, Epub 2020-10-20 | - |
dc.identifier.issn | 1077-2626 | - |
dc.identifier.uri | http://hdl.handle.net/10722/293191 | - |
dc.description.abstract | Segmenting arbitrary 3D objects into constituent parts that are structurally meaningful is a fundamental problem encountered in a wide range of computer graphics applications. Existing methods for 3D shape segmentation suffer from complex geometry processing and heavy computation caused by using low-level features and fragmented segmentation results due to the lack of global consideration. We present an efficient method, called SEG-MAT, based on the medial axis transform (MAT) of the input shape. Specifically, with the rich geometrical and structural information encoded in the MAT, we are able to develop a simple and principled approach to effectively identify the various types of junctions between different parts of a 3D shape. Extensive evaluations and comparisons show that our method outperforms the state-of-the-art methods in terms of segmentation quality and is also one order of magnitude faster | - |
dc.language | eng | - |
dc.publisher | Institute of Electrical and Electronics Engineers. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=2945 | - |
dc.relation.ispartof | IEEE Transactions on Visualization and Computer Graphics | - |
dc.rights | IEEE Transactions on Visualization and Computer Graphics. Copyright © Institute of Electrical and Electronics Engineers. | - |
dc.rights | ©20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | - |
dc.subject | Shape Analysis | - |
dc.subject | Shape Segmentation | - |
dc.subject | Medial Axis Transform | - |
dc.subject | Geometry | - |
dc.title | SEG-MAT: 3D Shape Segmentation Using Medial Axis Transform | - |
dc.type | Article | - |
dc.identifier.email | Wang, W: wenping@cs.hku.hk | - |
dc.identifier.authority | Wang, W=rp00186 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/TVCG.2020.3032566 | - |
dc.identifier.pmid | 33079671 | - |
dc.identifier.hkuros | 318866 | - |
dc.identifier.volume | Epub 2020-10-20 | - |
dc.identifier.isi | WOS:000790817100014 | - |
dc.publisher.place | United States | - |