Jan Hurtado, M. Gattass, A. Raposo, Jéferson Coêlho
{"title":"网格去噪的自适应补丁","authors":"Jan Hurtado, M. Gattass, A. Raposo, Jéferson Coêlho","doi":"10.1109/SIBGRAPI.2018.00007","DOIUrl":null,"url":null,"abstract":"The generation of triangular meshes typically introduces undesired noise which comes from different sources. Mesh denoising is a geometry processing task to remove this kind of distortion. To preserve the geometric fidelity of the desired mesh, a mesh denoising algorithm must maintain the object details while removing artificial high-frequencies from the surface. In this work, we propose a two-step algorithm which uses adaptive patches and bilateral filtering to denoise the normal vector field, and then update vertex positions fitting the faces to the denoised normals. The computation of the adaptive patches is our main contribution. We formulate this computation as local quadratic optimization problems that can be controlled by a set of parameters to obtain the desired behavior. We compared our proposal with several algorithms proposed in the literature using synthetic and real data. Our algorithm yields better results in general and is based on a formal mathematical formulation.","PeriodicalId":208985,"journal":{"name":"2018 31st SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Adaptive Patches for Mesh Denoising\",\"authors\":\"Jan Hurtado, M. Gattass, A. Raposo, Jéferson Coêlho\",\"doi\":\"10.1109/SIBGRAPI.2018.00007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The generation of triangular meshes typically introduces undesired noise which comes from different sources. Mesh denoising is a geometry processing task to remove this kind of distortion. To preserve the geometric fidelity of the desired mesh, a mesh denoising algorithm must maintain the object details while removing artificial high-frequencies from the surface. In this work, we propose a two-step algorithm which uses adaptive patches and bilateral filtering to denoise the normal vector field, and then update vertex positions fitting the faces to the denoised normals. The computation of the adaptive patches is our main contribution. We formulate this computation as local quadratic optimization problems that can be controlled by a set of parameters to obtain the desired behavior. We compared our proposal with several algorithms proposed in the literature using synthetic and real data. Our algorithm yields better results in general and is based on a formal mathematical formulation.\",\"PeriodicalId\":208985,\"journal\":{\"name\":\"2018 31st SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 31st SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIBGRAPI.2018.00007\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 31st SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIBGRAPI.2018.00007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The generation of triangular meshes typically introduces undesired noise which comes from different sources. Mesh denoising is a geometry processing task to remove this kind of distortion. To preserve the geometric fidelity of the desired mesh, a mesh denoising algorithm must maintain the object details while removing artificial high-frequencies from the surface. In this work, we propose a two-step algorithm which uses adaptive patches and bilateral filtering to denoise the normal vector field, and then update vertex positions fitting the faces to the denoised normals. The computation of the adaptive patches is our main contribution. We formulate this computation as local quadratic optimization problems that can be controlled by a set of parameters to obtain the desired behavior. We compared our proposal with several algorithms proposed in the literature using synthetic and real data. Our algorithm yields better results in general and is based on a formal mathematical formulation.