{"title":"各向异性几何中的实时可视化","authors":"Eryk Kopczynski, Dorota Celinska-Kopczynska","doi":"10.1080/10586458.2022.2050324","DOIUrl":null,"url":null,"abstract":"Abstract We present novel methods for real-time native geodesic rendering of anisotropic geometries and similar geometries, Nil, twisted . We also include partial results for the Berger sphere and explain why such real-time rendering of this geometry is difficult. Current approaches are not applicable for rendering complex shapes in these geometries, such as traditional 3D models, because of the computational complexity of ray-based approaches or significant rendering artifacts in older primitive-based approaches. We use tessellations to represent large shapes without numerical precision issues. Our efficient methods for computing the inverse exponential mapping are applicable not only for visualization but for games, physics simulations, and machine learning purposes as well.","PeriodicalId":50464,"journal":{"name":"Experimental Mathematics","volume":"31 1","pages":"1177 - 1196"},"PeriodicalIF":0.7000,"publicationDate":"2022-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Real-Time Visualization in Anisotropic Geometries\",\"authors\":\"Eryk Kopczynski, Dorota Celinska-Kopczynska\",\"doi\":\"10.1080/10586458.2022.2050324\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract We present novel methods for real-time native geodesic rendering of anisotropic geometries and similar geometries, Nil, twisted . We also include partial results for the Berger sphere and explain why such real-time rendering of this geometry is difficult. Current approaches are not applicable for rendering complex shapes in these geometries, such as traditional 3D models, because of the computational complexity of ray-based approaches or significant rendering artifacts in older primitive-based approaches. We use tessellations to represent large shapes without numerical precision issues. Our efficient methods for computing the inverse exponential mapping are applicable not only for visualization but for games, physics simulations, and machine learning purposes as well.\",\"PeriodicalId\":50464,\"journal\":{\"name\":\"Experimental Mathematics\",\"volume\":\"31 1\",\"pages\":\"1177 - 1196\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2022-04-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Experimental Mathematics\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1080/10586458.2022.2050324\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Experimental Mathematics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/10586458.2022.2050324","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS","Score":null,"Total":0}
Abstract We present novel methods for real-time native geodesic rendering of anisotropic geometries and similar geometries, Nil, twisted . We also include partial results for the Berger sphere and explain why such real-time rendering of this geometry is difficult. Current approaches are not applicable for rendering complex shapes in these geometries, such as traditional 3D models, because of the computational complexity of ray-based approaches or significant rendering artifacts in older primitive-based approaches. We use tessellations to represent large shapes without numerical precision issues. Our efficient methods for computing the inverse exponential mapping are applicable not only for visualization but for games, physics simulations, and machine learning purposes as well.
期刊介绍:
Experimental Mathematics publishes original papers featuring formal results inspired by experimentation, conjectures suggested by experiments, and data supporting significant hypotheses.
Experiment has always been, and increasingly is, an important method of mathematical discovery. (Gauss declared that his way of arriving at mathematical truths was "through systematic experimentation.") Yet this tends to be concealed by the tradition of presenting only elegant, fully developed, and rigorous results.
Experimental Mathematics was founded in the belief that theory and experiment feed on each other, and that the mathematical community stands to benefit from a more complete exposure to the experimental process. The early sharing of insights increases the possibility that they will lead to theorems: An interesting conjecture is often formulated by a researcher who lacks the techniques to formalize a proof, while those who have the techniques at their fingertips have been looking elsewhere. Even when the person who had the initial insight goes on to find a proof, a discussion of the heuristic process can be of help, or at least of interest, to other researchers. There is value not only in the discovery itself, but also in the road that leads to it.