Efficient GPU out-of-core visualization of large-scale CAD models with voxel representations. (September 2016) - Xue, Junjie
Highlights: An efficient GPU out-of-core rendering framework for large-scale model is proposed. LOD geometries are compressed using an aggressive compression scheme. Voxel representations are used for efficient visibility query and shadow rendering. Integration of LOD with visibility query ensures high efficiency of data streaming. Abstract: Visualizing large-scale CAD models has been recognized as one of the most challenging tasks in engineering software development. Due to the constraints of limited GPU memory size and computation capacity, the CAD model of a complex product with hundreds of millions triangles cannot be loaded and rendered in real-time using most of modern GPUs. In this paper, an efficient voxel assisted GPU out-of-core framework is proposed for visualizing massive CAD models interactively. In order to reduce memory cost and improve efficiency of data streaming, a parallel off-line geometry attributes compression scheme is introduced to minimize the storage cost of each primitive by quantifying the LOD (levels of detail) geometries into a highly compact format. At the rendering stage, voxel representation is utilized to query visible objects by efficient ray casting algorithms, which is distinguishable from primitive or bounding box based visibility culling methods. The voxel representation is also utilized for shadow ray intersection test to generate soft shadow effect which results in enhancement of rendering realism. A prototype software system is developed to preprocess and render massive models with the proposed framework. Experimental results show that users can interactively visualize CAD models with hundreds of millions of triangles at high frame rates using our framework.