{"title":"彭纳坐标中的无缝参数化","authors":"Ryan Capouellez, Denis Zorin","doi":"arxiv-2407.21342","DOIUrl":null,"url":null,"abstract":"We introduce a conceptually simple and efficient algorithm for seamless\nparametrization, a key element in constructing quad layouts and texture charts\non surfaces. More specifically, we consider the construction of\nparametrizations with prescribed holonomy signatures i.e., a set of angles at\nsingularities, and rotations along homology loops, preserving which is\nessential for constructing parametrizations following an input field, as well\nas for user control of the parametrization structure. Our algorithm performs\nexceptionally well on a large dataset based on Thingi10k [Zhou and Jacobson\n2016], (16156 meshes) as well as on a challenging smaller dataset of [Myles et\nal. 2014], converging, on average, in 9 iterations. Although the algorithm\nlacks a formal mathematical guarantee, presented empirical evidence and the\nconnections between convex optimization and closely related algorithms, suggest\nthat a similar formulation can be found for this algorithm in the future.","PeriodicalId":501174,"journal":{"name":"arXiv - CS - Graphics","volume":"7 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Seamless Parametrization in Penner Coordinates\",\"authors\":\"Ryan Capouellez, Denis Zorin\",\"doi\":\"arxiv-2407.21342\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce a conceptually simple and efficient algorithm for seamless\\nparametrization, a key element in constructing quad layouts and texture charts\\non surfaces. More specifically, we consider the construction of\\nparametrizations with prescribed holonomy signatures i.e., a set of angles at\\nsingularities, and rotations along homology loops, preserving which is\\nessential for constructing parametrizations following an input field, as well\\nas for user control of the parametrization structure. Our algorithm performs\\nexceptionally well on a large dataset based on Thingi10k [Zhou and Jacobson\\n2016], (16156 meshes) as well as on a challenging smaller dataset of [Myles et\\nal. 2014], converging, on average, in 9 iterations. Although the algorithm\\nlacks a formal mathematical guarantee, presented empirical evidence and the\\nconnections between convex optimization and closely related algorithms, suggest\\nthat a similar formulation can be found for this algorithm in the future.\",\"PeriodicalId\":501174,\"journal\":{\"name\":\"arXiv - CS - Graphics\",\"volume\":\"7 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Graphics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2407.21342\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Graphics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.21342","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We introduce a conceptually simple and efficient algorithm for seamless
parametrization, a key element in constructing quad layouts and texture charts
on surfaces. More specifically, we consider the construction of
parametrizations with prescribed holonomy signatures i.e., a set of angles at
singularities, and rotations along homology loops, preserving which is
essential for constructing parametrizations following an input field, as well
as for user control of the parametrization structure. Our algorithm performs
exceptionally well on a large dataset based on Thingi10k [Zhou and Jacobson
2016], (16156 meshes) as well as on a challenging smaller dataset of [Myles et
al. 2014], converging, on average, in 9 iterations. Although the algorithm
lacks a formal mathematical guarantee, presented empirical evidence and the
connections between convex optimization and closely related algorithms, suggest
that a similar formulation can be found for this algorithm in the future.