Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Skeleton-based seam computation for triangulated surface parameterization

Zhu, Xu-Ping, Hu, Shi-Min and Martin, Ralph Robert 2003. Skeleton-based seam computation for triangulated surface parameterization. Presented at: 10th IMA International Conference, Leeds, UK, 15-17 September 2003. Published in: Wilson, M and Martin, Ralph Robert eds. Mathematics of surfaces : 10th IMA international conference, Leeds, UK, September 15-17, 2003 , proceedings. Lecture notes in computer science , vol. 2768. Berlin-Heidelberg: Springer Verlag, pp. 1-13. 10.1007/978-3-540-39422-8_1

[img]
Preview
PDF - Accepted Post-Print Version
Available under License Creative Commons Attribution.

Download (375kB) | Preview

Abstract

Mesh parameterization is a key problem in digital geometry processing. By cutting a surface along a set of edges (a seam), one can map an arbitrary topology surface mesh to a single chart. Unfortunately, high distortion occurs when protrusions of the surface (such as fingers of a hand and horses’ legs) are flattened into a plane. This paper presents a novel skeleton-based algorithm for computing a seam on a triangulated surface. The seam produced is a full component Steiner tree in a graph constructed from the original mesh. By generating the seam so that all extremal vertices are leaves of the seam, we can obtain good parametrization with low distortion.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Additional Information: PDF uploaded in accordance with publisher's policy http://www.springer.com/gp/open-access/authors-rights/self-archiving-policy/2124 [accessed 04/12/2014]
Publisher: Springer Verlag
ISBN: 3540200533
Date of First Compliant Deposit: 30 March 2016
Last Modified: 04 Jun 2017 04:03
URI: http://orca.cf.ac.uk/id/eprint/31789

Citation Data

Cited 4 times in Google Scholar. View in Google Scholar

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics