A variational approach for feature-aware B-spline curve design on surface meshes

Robust curve design on surface meshes with flexible controls is useful in a wide range of applications but remains challenging. Most existing methods fall into one of the two strategies: one is to discretize a curve into a polyline, which is then optimized, and the other is to directly design smooth...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:The Visual computer 2023-08, Vol.39 (8), p.3767-3781
Hauptverfasser: Xu, Rongyan, Jin, Yao, Zhang, Huaxiong, Zhang, Yun, Lai, Yu-kun, Zhu, Zhe, Zhang, Fang-Lue
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 3781
container_issue 8
container_start_page 3767
container_title The Visual computer
container_volume 39
creator Xu, Rongyan
Jin, Yao
Zhang, Huaxiong
Zhang, Yun
Lai, Yu-kun
Zhu, Zhe
Zhang, Fang-Lue
description Robust curve design on surface meshes with flexible controls is useful in a wide range of applications but remains challenging. Most existing methods fall into one of the two strategies: one is to discretize a curve into a polyline, which is then optimized, and the other is to directly design smooth splines on meshes. While the former approach usually needs a sufficiently dense sampling of curve points, which is computational costly, the latter approach relaxes the sampling requirement but suffers from the lack of user control. To tackle these problems, we proposed a variational method for designing feature-aware B-spline curves on surface meshes. Given the recent advances in shell space construction methods, we could relax the B-spline curve inside a simplified shell mesh and evaluate its distance to the surface using equipped bijective mapping. To effectively minimize the distance between the curve and the surface, with additional controls in the form of both internal and external constraints, we applied the interior point method and adaptively inserted knots of the spline to increase its freedom and adjust the weighting during the iterations. When the curve is close enough to the surface, it can be efficiently sampled at any resolution and robustly projected to the surface. Experiments show that our method is more robust, has higher flexibility, and generates smoother results than existing methods.
doi_str_mv 10.1007/s00371-023-03001-x
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2918136779</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2918136779</sourcerecordid><originalsourceid>FETCH-LOGICAL-c314t-7beec41aa1f5859fbd34975cc6f55642b65d0cd65f8aa7c2cc99f7887fe81e0f3</originalsourceid><addsrcrecordid>eNp9kDtPwzAUhS0EEqXwB5gsMRv8iGN7LBUvqRIMMFuuc92mapNgJ6X8ewxBYmO6y3eOzv0QumT0mlGqbhKlQjFCuSBUUMrI4QhNWCE44YLJYzShTGnClTan6CylTUaUKswEvczw3sXa9XXbuC12XRdb59c4tBEHcP0QgbgPFwHfktRt6wawH-IecAWpXjW4bXAaYnAe8A7SGtI5Oglum-Di907R2_3d6_yRLJ4fnuazBfGCFT1RSwBfMOdYkFqasKxEYZT0vgxSlgVflrKivipl0M4pz703JiitVQDNgAYxRVdjbx78PkDq7aYdYv4hWW6YZqJUymSKj5SPbUoRgu1ivXPx0zJqv83Z0ZzN5uyPOXvIITGGUoabFcS_6n9SX77ociw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2918136779</pqid></control><display><type>article</type><title>A variational approach for feature-aware B-spline curve design on surface meshes</title><source>Springer Nature - Complete Springer Journals</source><source>ProQuest Central UK/Ireland</source><source>ProQuest Central</source><creator>Xu, Rongyan ; Jin, Yao ; Zhang, Huaxiong ; Zhang, Yun ; Lai, Yu-kun ; Zhu, Zhe ; Zhang, Fang-Lue</creator><creatorcontrib>Xu, Rongyan ; Jin, Yao ; Zhang, Huaxiong ; Zhang, Yun ; Lai, Yu-kun ; Zhu, Zhe ; Zhang, Fang-Lue</creatorcontrib><description>Robust curve design on surface meshes with flexible controls is useful in a wide range of applications but remains challenging. Most existing methods fall into one of the two strategies: one is to discretize a curve into a polyline, which is then optimized, and the other is to directly design smooth splines on meshes. While the former approach usually needs a sufficiently dense sampling of curve points, which is computational costly, the latter approach relaxes the sampling requirement but suffers from the lack of user control. To tackle these problems, we proposed a variational method for designing feature-aware B-spline curves on surface meshes. Given the recent advances in shell space construction methods, we could relax the B-spline curve inside a simplified shell mesh and evaluate its distance to the surface using equipped bijective mapping. To effectively minimize the distance between the curve and the surface, with additional controls in the form of both internal and external constraints, we applied the interior point method and adaptively inserted knots of the spline to increase its freedom and adjust the weighting during the iterations. When the curve is close enough to the surface, it can be efficiently sampled at any resolution and robustly projected to the surface. Experiments show that our method is more robust, has higher flexibility, and generates smoother results than existing methods.</description><identifier>ISSN: 0178-2789</identifier><identifier>EISSN: 1432-2315</identifier><identifier>DOI: 10.1007/s00371-023-03001-x</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Algorithms ; Artificial Intelligence ; B spline functions ; Computer Graphics ; Computer Science ; Design ; Energy ; Euclidean space ; Image Processing and Computer Vision ; Knots ; Methods ; Optimization ; Original Article ; Partial differential equations ; Robustness ; Sampling</subject><ispartof>The Visual computer, 2023-08, Vol.39 (8), p.3767-3781</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c314t-7beec41aa1f5859fbd34975cc6f55642b65d0cd65f8aa7c2cc99f7887fe81e0f3</cites><orcidid>0000-0002-2902-9662</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00371-023-03001-x$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2918136779?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,776,780,21368,27903,27904,33723,41467,42536,43784,51298,64362,64366,72216</link.rule.ids></links><search><creatorcontrib>Xu, Rongyan</creatorcontrib><creatorcontrib>Jin, Yao</creatorcontrib><creatorcontrib>Zhang, Huaxiong</creatorcontrib><creatorcontrib>Zhang, Yun</creatorcontrib><creatorcontrib>Lai, Yu-kun</creatorcontrib><creatorcontrib>Zhu, Zhe</creatorcontrib><creatorcontrib>Zhang, Fang-Lue</creatorcontrib><title>A variational approach for feature-aware B-spline curve design on surface meshes</title><title>The Visual computer</title><addtitle>Vis Comput</addtitle><description>Robust curve design on surface meshes with flexible controls is useful in a wide range of applications but remains challenging. Most existing methods fall into one of the two strategies: one is to discretize a curve into a polyline, which is then optimized, and the other is to directly design smooth splines on meshes. While the former approach usually needs a sufficiently dense sampling of curve points, which is computational costly, the latter approach relaxes the sampling requirement but suffers from the lack of user control. To tackle these problems, we proposed a variational method for designing feature-aware B-spline curves on surface meshes. Given the recent advances in shell space construction methods, we could relax the B-spline curve inside a simplified shell mesh and evaluate its distance to the surface using equipped bijective mapping. To effectively minimize the distance between the curve and the surface, with additional controls in the form of both internal and external constraints, we applied the interior point method and adaptively inserted knots of the spline to increase its freedom and adjust the weighting during the iterations. When the curve is close enough to the surface, it can be efficiently sampled at any resolution and robustly projected to the surface. Experiments show that our method is more robust, has higher flexibility, and generates smoother results than existing methods.</description><subject>Algorithms</subject><subject>Artificial Intelligence</subject><subject>B spline functions</subject><subject>Computer Graphics</subject><subject>Computer Science</subject><subject>Design</subject><subject>Energy</subject><subject>Euclidean space</subject><subject>Image Processing and Computer Vision</subject><subject>Knots</subject><subject>Methods</subject><subject>Optimization</subject><subject>Original Article</subject><subject>Partial differential equations</subject><subject>Robustness</subject><subject>Sampling</subject><issn>0178-2789</issn><issn>1432-2315</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kDtPwzAUhS0EEqXwB5gsMRv8iGN7LBUvqRIMMFuuc92mapNgJ6X8ewxBYmO6y3eOzv0QumT0mlGqbhKlQjFCuSBUUMrI4QhNWCE44YLJYzShTGnClTan6CylTUaUKswEvczw3sXa9XXbuC12XRdb59c4tBEHcP0QgbgPFwHfktRt6wawH-IecAWpXjW4bXAaYnAe8A7SGtI5Oglum-Di907R2_3d6_yRLJ4fnuazBfGCFT1RSwBfMOdYkFqasKxEYZT0vgxSlgVflrKivipl0M4pz703JiitVQDNgAYxRVdjbx78PkDq7aYdYv4hWW6YZqJUymSKj5SPbUoRgu1ivXPx0zJqv83Z0ZzN5uyPOXvIITGGUoabFcS_6n9SX77ociw</recordid><startdate>20230801</startdate><enddate>20230801</enddate><creator>Xu, Rongyan</creator><creator>Jin, Yao</creator><creator>Zhang, Huaxiong</creator><creator>Zhang, Yun</creator><creator>Lai, Yu-kun</creator><creator>Zhu, Zhe</creator><creator>Zhang, Fang-Lue</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><orcidid>https://orcid.org/0000-0002-2902-9662</orcidid></search><sort><creationdate>20230801</creationdate><title>A variational approach for feature-aware B-spline curve design on surface meshes</title><author>Xu, Rongyan ; Jin, Yao ; Zhang, Huaxiong ; Zhang, Yun ; Lai, Yu-kun ; Zhu, Zhe ; Zhang, Fang-Lue</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c314t-7beec41aa1f5859fbd34975cc6f55642b65d0cd65f8aa7c2cc99f7887fe81e0f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Artificial Intelligence</topic><topic>B spline functions</topic><topic>Computer Graphics</topic><topic>Computer Science</topic><topic>Design</topic><topic>Energy</topic><topic>Euclidean space</topic><topic>Image Processing and Computer Vision</topic><topic>Knots</topic><topic>Methods</topic><topic>Optimization</topic><topic>Original Article</topic><topic>Partial differential equations</topic><topic>Robustness</topic><topic>Sampling</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xu, Rongyan</creatorcontrib><creatorcontrib>Jin, Yao</creatorcontrib><creatorcontrib>Zhang, Huaxiong</creatorcontrib><creatorcontrib>Zhang, Yun</creatorcontrib><creatorcontrib>Lai, Yu-kun</creatorcontrib><creatorcontrib>Zhu, Zhe</creatorcontrib><creatorcontrib>Zhang, Fang-Lue</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>The Visual computer</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xu, Rongyan</au><au>Jin, Yao</au><au>Zhang, Huaxiong</au><au>Zhang, Yun</au><au>Lai, Yu-kun</au><au>Zhu, Zhe</au><au>Zhang, Fang-Lue</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A variational approach for feature-aware B-spline curve design on surface meshes</atitle><jtitle>The Visual computer</jtitle><stitle>Vis Comput</stitle><date>2023-08-01</date><risdate>2023</risdate><volume>39</volume><issue>8</issue><spage>3767</spage><epage>3781</epage><pages>3767-3781</pages><issn>0178-2789</issn><eissn>1432-2315</eissn><abstract>Robust curve design on surface meshes with flexible controls is useful in a wide range of applications but remains challenging. Most existing methods fall into one of the two strategies: one is to discretize a curve into a polyline, which is then optimized, and the other is to directly design smooth splines on meshes. While the former approach usually needs a sufficiently dense sampling of curve points, which is computational costly, the latter approach relaxes the sampling requirement but suffers from the lack of user control. To tackle these problems, we proposed a variational method for designing feature-aware B-spline curves on surface meshes. Given the recent advances in shell space construction methods, we could relax the B-spline curve inside a simplified shell mesh and evaluate its distance to the surface using equipped bijective mapping. To effectively minimize the distance between the curve and the surface, with additional controls in the form of both internal and external constraints, we applied the interior point method and adaptively inserted knots of the spline to increase its freedom and adjust the weighting during the iterations. When the curve is close enough to the surface, it can be efficiently sampled at any resolution and robustly projected to the surface. Experiments show that our method is more robust, has higher flexibility, and generates smoother results than existing methods.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s00371-023-03001-x</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-2902-9662</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0178-2789
ispartof The Visual computer, 2023-08, Vol.39 (8), p.3767-3781
issn 0178-2789
1432-2315
language eng
recordid cdi_proquest_journals_2918136779
source Springer Nature - Complete Springer Journals; ProQuest Central UK/Ireland; ProQuest Central
subjects Algorithms
Artificial Intelligence
B spline functions
Computer Graphics
Computer Science
Design
Energy
Euclidean space
Image Processing and Computer Vision
Knots
Methods
Optimization
Original Article
Partial differential equations
Robustness
Sampling
title A variational approach for feature-aware B-spline curve design on surface meshes
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-22T01%3A55%3A11IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20variational%20approach%20for%20feature-aware%20B-spline%20curve%20design%20on%20surface%20meshes&rft.jtitle=The%20Visual%20computer&rft.au=Xu,%20Rongyan&rft.date=2023-08-01&rft.volume=39&rft.issue=8&rft.spage=3767&rft.epage=3781&rft.pages=3767-3781&rft.issn=0178-2789&rft.eissn=1432-2315&rft_id=info:doi/10.1007/s00371-023-03001-x&rft_dat=%3Cproquest_cross%3E2918136779%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2918136779&rft_id=info:pmid/&rfr_iscdi=true