Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Octrees for faster isosurface generation
ACM Transactions on Graphics (TOG)
Octree-based decimation of marching cubes surfaces
Proceedings of the 7th conference on Visualization '96
Frame-to-frame coherence and the hidden surface computation: constraints for a convex world
ACM Transactions on Graphics (TOG)
Visualization Handbook
A framework for fast and accurate collision detection for haptic interaction
SIGGRAPH '05 ACM SIGGRAPH 2005 Courses
TimeLine and visualization of multiple-data sets and the visualization querying challenge
Journal of Visual Languages and Computing
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The paper deals with visualization of multiple datasets by exploiting data coherency among the datasets under consideration to address the issues related to storage and computation. The proposed data coherency approach utilizes the similarities among datasets by using the already generated polygon data for one or more reference datasets to approximate the isosurfaces of similar regions in other datasets. For finding the similarity among the multiple datasets, we use the octree data structure and compare datasets block by block. Blocks of a non-reference dataset, whose difference from the corresponding blocks of the reference dataset is within the user defined tolerance level, we use the already extracted polygon data for the reference data blocks to approximate the isosurfaces. Thus, only those non-reference data blocks, which differ from the reference blocks, are processed. Thereby, we reduce the number of polygons to represent the isosurfaces. To overcome the problem of cracks in thus extracted isosurfaces, we use a simple approach of overlapping at the interface between the directly processed and approximated portions of the isosurfaces. We have explored the effects of various factors including the data coherency condition, tolerance level and block size on the performance. Our results show that the proposed data coherency technique considerably improves the overall performance.