Occlusion Culling in OpenSG PLUS

Abstract

Very large polygonal models are frequently used in scientific computing, mechanical engineering, or virtual medicine. An effective technique to handle these large models is occlusion culling. Like most large model techniques, occlusion culling trades overhead costs with the rendering costs of the possibly occluded geometry.

In this paper, we present occlusion culling techniques for OpenSG. These techniques utilize OpenGL or OpenGL extensions to determine occlusion information. Techniques utilizing image-space and temporal coherence are used to optimize occlusion query efficiency. Only the standard OpenSG data structures are used and no precomputation is necessary for the presented techniques.

Introduction

Interactive visualization of large datasets in scientific computing, mechanical engineering, or medical imaging is a major objective of many rendering techniques. Most of them reduce the number of polygons, others are using sampling techniques like point sampling or ray tracing. To reduce the number of polygons, level-of-detail [1] or impostor techniques can be used. Occlusion culling is another approach for rapid visualization of large datasets. Here, hidden parts of a scene are detected and excluded from the rendering process. In this paper, we will present occlusion culling techniques implemented in OpenSG PLUS.

OpenSG [2] is a portable scene graph toolkit with a focus on real-time rendering. Within the OpenSG PLUS project, OpenSG is enhanced with large scene support, high-level rendering primitives and high-level shading. The here presented occlusion culling techniques are part of the large scene support.

The remainder of this paper is organized as follows: the next section briefly reviews related toolkits for visualization and occlusion culling techniques. Section 3 describes the occlusion query techniques and their features. Results are shown in Section 4, followed by a conclusion in Section 5.