Title
Parallel View-Dependent Isosurface Extraction Using Multi-Pass Occlusion Culling
Document Type
Conference Presentation
Department
Computer Science
Conference Title
IEEE Symposium in Parallel and Large Data Visualization and Graphics
Location
San Diego, CA
Conference Dates
October 22 - 23, 2001
Date of Presentation
10-22-2001
Abstract
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.
First Page
67
Last Page
74
DOI
10.1109/PVGS.2001.964406
Recommended Citation
Gao, J.,
&
Shen, H.
(2001).
Parallel View-Dependent Isosurface Extraction Using Multi-Pass Occlusion Culling.
Paper presented at IEEE Symposium in Parallel and Large Data Visualization and Graphics in San Diego, CA.
https://scholarlycommons.pacific.edu/soecs-facpres/84
