We present an efficient framework for the high-quality rendering of discretely sampled surface-based objects with refractive effects. This requires an accurate estimation of the refraction coefficients, paired with efficient and accurate surface detection, space traversal, and backdrop image sampling. Our framework achieves these goals, by employing a high-quality spline-based filter in conjunction with a novel filtered octree space decomposition with pre-classified cells that is carefully matched to the filter and voxel neighborhood characteristics. Here, we benefit greatly from the non-negativity of the B-spline kernel. Finally, we describe an innovative scheme that achieves the high quality of pixel super-sampling on a flat backdrop plane without the overhead of tracing the actual rays across the refractive object.
{"title":"Accelerated, high-quality refraction computations for volume graphics","authors":"Shengying Li, K. Mueller","doi":"10.2312/VG/VG05/073-081","DOIUrl":"https://doi.org/10.2312/VG/VG05/073-081","url":null,"abstract":"We present an efficient framework for the high-quality rendering of discretely sampled surface-based objects with refractive effects. This requires an accurate estimation of the refraction coefficients, paired with efficient and accurate surface detection, space traversal, and backdrop image sampling. Our framework achieves these goals, by employing a high-quality spline-based filter in conjunction with a novel filtered octree space decomposition with pre-classified cells that is carefully matched to the filter and voxel neighborhood characteristics. Here, we benefit greatly from the non-negativity of the B-spline kernel. Finally, we describe an innovative scheme that achieves the high quality of pixel super-sampling on a flat backdrop plane without the overhead of tracing the actual rays across the refractive object.","PeriodicalId":443333,"journal":{"name":"Fourth International Workshop on Volume Graphics, 2005.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2005-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117261798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yuriko Takeshima, Shigeo Takahashi, I. Fujishiro, G. Nielson
Recent development in the design of multi-dimensional transfer functions allows us to automatically generate comprehensible visualization images of given volumes by taking into account local features such as differentials and curvatures. However, especially when visualizing volumes obtained by scientific simulations, observers usually exploit their knowledge about the simulation settings as the clues to the effective control of visualization parameters for their own specific purposes. This paper therefore presents an objective-based framework for visualizing simulated volume datasets by introducing a new set of topological attributes. These topological attributes are calculated from the level-set graph of a given volume dataset, and thus differ from the conventional local attributes in that they also illuminate the global structure of the volume. The present framework provides a systematic means of emphasizing the underlying volume features, such as nested structures of isosurfaces, configuration of isosurface trajectories, and transitions of isosurface's topological type. Several combinations of the topological attributes together with the associated transfer function designs are devised and applied to real simulated datasets in order to demonstrate the feasibility of the present framework.
{"title":"Introducing topological attributes for objective-based visualization of simulated datasets","authors":"Yuriko Takeshima, Shigeo Takahashi, I. Fujishiro, G. Nielson","doi":"10.2312/VG/VG05/137-145","DOIUrl":"https://doi.org/10.2312/VG/VG05/137-145","url":null,"abstract":"Recent development in the design of multi-dimensional transfer functions allows us to automatically generate comprehensible visualization images of given volumes by taking into account local features such as differentials and curvatures. However, especially when visualizing volumes obtained by scientific simulations, observers usually exploit their knowledge about the simulation settings as the clues to the effective control of visualization parameters for their own specific purposes. This paper therefore presents an objective-based framework for visualizing simulated volume datasets by introducing a new set of topological attributes. These topological attributes are calculated from the level-set graph of a given volume dataset, and thus differ from the conventional local attributes in that they also illuminate the global structure of the volume. The present framework provides a systematic means of emphasizing the underlying volume features, such as nested structures of isosurfaces, configuration of isosurface trajectories, and transitions of isosurface's topological type. Several combinations of the topological attributes together with the associated transfer function designs are devised and applied to real simulated datasets in order to demonstrate the feasibility of the present framework.","PeriodicalId":443333,"journal":{"name":"Fourth International Workshop on Volume Graphics, 2005.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2005-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130373310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A new method for robust generation of distance fields from triangle meshes is presented. Graphics hardware is used to accelerate a technique for generating layered depth images. From multiple layered depth images, a binary volume and a point representation are extracted. The point information is then used to convert the binary volume into a distance field. The method is robust and handles holes, spurious triangles and ambiguities. Moreover, the method lends itself to Boolean operations between solids. Since a point cloud as well as a signed distance is generated, it is possible to extract an iso-surface of the distance field and fit it to the point set. Using this method, one may recover sharp edge information. Examples are given where the method for generating distance fields coupled with mesh fitting is used to perform Boolean and morphological operations on triangle meshes.
{"title":"Robust generation of signed distance fields from triangle meshes","authors":"J. Baerentzen","doi":"10.1109/vg.2005.194111","DOIUrl":"https://doi.org/10.1109/vg.2005.194111","url":null,"abstract":"A new method for robust generation of distance fields from triangle meshes is presented. Graphics hardware is used to accelerate a technique for generating layered depth images. From multiple layered depth images, a binary volume and a point representation are extracted. The point information is then used to convert the binary volume into a distance field. The method is robust and handles holes, spurious triangles and ambiguities. Moreover, the method lends itself to Boolean operations between solids. Since a point cloud as well as a signed distance is generated, it is possible to extract an iso-surface of the distance field and fit it to the point set. Using this method, one may recover sharp edge information. Examples are given where the method for generating distance fields coupled with mesh fitting is used to perform Boolean and morphological operations on triangle meshes.","PeriodicalId":443333,"journal":{"name":"Fourth International Workshop on Volume Graphics, 2005.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121327049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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