{"title":"Chapter 6: Multiresolution Representation and Deformation of Very Large Volume Datasets Based on Haar Wavelets","authors":"H. Xavier, T. Sebastien","doi":"10.1109/GMAI.2008.26","DOIUrl":null,"url":null,"abstract":"In a virtual sculpture project, we would like to sculpt in real-time very large 3D objects sampled in volume elements (voxels). The drawback of this kind of representation is the important number of voxels required to represent very large and detailed objects. Consequently, that entails important memory cost and computation time issues. In order to allow real-time performance, we propose in this paper a new multiresolution model that combines octree and wavelet: a 3D object is roughly sampled in an octree, where each leaf containing data is thinly sampled thanks to a 3D Haar wavelet transform.","PeriodicalId":393559,"journal":{"name":"2008 3rd International Conference on Geometric Modeling and Imaging","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 3rd International Conference on Geometric Modeling and Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GMAI.2008.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In a virtual sculpture project, we would like to sculpt in real-time very large 3D objects sampled in volume elements (voxels). The drawback of this kind of representation is the important number of voxels required to represent very large and detailed objects. Consequently, that entails important memory cost and computation time issues. In order to allow real-time performance, we propose in this paper a new multiresolution model that combines octree and wavelet: a 3D object is roughly sampled in an octree, where each leaf containing data is thinly sampled thanks to a 3D Haar wavelet transform.