Parallel View-Dependent Isosurface Extraction Using Multi-Pass Occlusion Culling

Authors

Jinzhu Gao, University of the PacificFollow
Han-Wei Shen, Ohio State University

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