Yuan-Yuan Cheng, Qing Fang, Ligang Liu, Xiao-Ming Fu
{"title":"高斯图象等高线上的可展开逼近。","authors":"Yuan-Yuan Cheng, Qing Fang, Ligang Liu, Xiao-Ming Fu","doi":"10.1109/TVCG.2025.3566887","DOIUrl":null,"url":null,"abstract":"<p><p>We propose a novel method to generate developable approximations for triangular meshes. Instead of fitting the Gauss image using a geodesic circle in the local neighborhood, we apply a nonlinear dimensionality reduction method, called Isomap, to use a general curve on the sphere for fitting. This brings us a larger space to represent the Gauss image in the local neighborhood as a 1D structure. Specifically, each triangle is assigned a target normal after local fitting; then, we deform the mesh to approach the target normal globally. By iteratively performing fitting and deformation, we obtain the developable approximation. We demonstrate the feasibility and effectiveness of our method over various examples. Compared to the state-of-the-art methods, our results exhibit a higher fidelity to the input mesh while possessing more prominent and visually distinct undevelopable seam curves.</p>","PeriodicalId":94035,"journal":{"name":"IEEE transactions on visualization and computer graphics","volume":"PP ","pages":""},"PeriodicalIF":6.5000,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Developable Approximation via Isomap on Gauss Image.\",\"authors\":\"Yuan-Yuan Cheng, Qing Fang, Ligang Liu, Xiao-Ming Fu\",\"doi\":\"10.1109/TVCG.2025.3566887\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>We propose a novel method to generate developable approximations for triangular meshes. Instead of fitting the Gauss image using a geodesic circle in the local neighborhood, we apply a nonlinear dimensionality reduction method, called Isomap, to use a general curve on the sphere for fitting. This brings us a larger space to represent the Gauss image in the local neighborhood as a 1D structure. Specifically, each triangle is assigned a target normal after local fitting; then, we deform the mesh to approach the target normal globally. By iteratively performing fitting and deformation, we obtain the developable approximation. We demonstrate the feasibility and effectiveness of our method over various examples. Compared to the state-of-the-art methods, our results exhibit a higher fidelity to the input mesh while possessing more prominent and visually distinct undevelopable seam curves.</p>\",\"PeriodicalId\":94035,\"journal\":{\"name\":\"IEEE transactions on visualization and computer graphics\",\"volume\":\"PP \",\"pages\":\"\"},\"PeriodicalIF\":6.5000,\"publicationDate\":\"2025-05-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE transactions on visualization and computer graphics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TVCG.2025.3566887\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE transactions on visualization and computer graphics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TVCG.2025.3566887","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Developable Approximation via Isomap on Gauss Image.
We propose a novel method to generate developable approximations for triangular meshes. Instead of fitting the Gauss image using a geodesic circle in the local neighborhood, we apply a nonlinear dimensionality reduction method, called Isomap, to use a general curve on the sphere for fitting. This brings us a larger space to represent the Gauss image in the local neighborhood as a 1D structure. Specifically, each triangle is assigned a target normal after local fitting; then, we deform the mesh to approach the target normal globally. By iteratively performing fitting and deformation, we obtain the developable approximation. We demonstrate the feasibility and effectiveness of our method over various examples. Compared to the state-of-the-art methods, our results exhibit a higher fidelity to the input mesh while possessing more prominent and visually distinct undevelopable seam curves.