Parallel view-dependent isosurface extraction using multi-pass occlusion culling

Presents a parallel algorithm that can effectively extract only the visible portion of isosurfaces. The main focus of our research is to devise a load-balanced and output-sensitive algorithm, that is, each processor will generate approximately the same amount of triangles, and cells that do not cont...

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Vydáno v:IEEE Parallel and Large Data Visualization and Graphics Symposium 2001 s. 67 - 152
Hlavní autoři: Jinzhu Gao, Han-Wei Shen
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 2001
Témata:
Acceleration
Clustering algorithms
Computer graphics
Concurrent computing
Data mining
Data structures
Hardware
Isosurfaces
Large-scale systems
Partitioning algorithms
ISBN:0780372239, 9780780372238
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Shrnutí:Presents a parallel algorithm that can effectively extract only the visible portion of isosurfaces. The main focus of our research is to devise a load-balanced and output-sensitive algorithm, that is, each processor will generate approximately the same amount of triangles, and cells that do not contain the visible isosurface will not be visited. A multi-pass algorithm is proposed to achieve these goals. In the algorithm, we first use an octree data structure to rapidly skip the empty cells. An image space visibility culling technique is then used to identify the visible isosurface cells in a progressive manner. To distribute the workload, we use a binary image space partitioning method to ensure that each processor will generate approximately the same amount of triangles. Isosurface extraction and visibility update are performed in parallel to reduce the total computation time. In addition to reducing the size of output geometry and accelerating the process of isosurface extraction, the multi-pass nature of our algorithm can also be used to perform time-critical computation.
ISBN:0780372239
9780780372238
DOI:10.1109/PVGS.2001.964406