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An Easy Viewer for Out-of-core Visualization of Huge Point-sampled Models
| Content Provider | CiteSeerX |
|---|---|
| Author | Zha, Hongbin Meng, Fang |
| Abstract | In this paper, we propose a viewer for huge point-sampled models by combining out-of-core technologies with view-dependent level-of-detail (LOD) control. This viewer is designed on the basis of a multiresolution data structure we have developed for gaze-guided visualization and transmission of 3D point sets. In order to reduce memory loads for huge point sets on general PC platforms, we introduce a partition-based out-of-core strategy to balance usage of main and external memories. At first, the data surface is partitioned into small blocks and points in each block are reorganized into error-controlled LODs by hierarchical clustering and LOD organization. In the interactive rendering process, a data block scheduling algorithm is used to realize the view-dependent paging. Experimental results show that the viewer can perform interactive visualization of huge point models on commodity graphics platforms with ease. 1. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Data Surface Huge Point Set Gaze-guided Visualization Interactive Rendering Process Point Set Easy Viewer Memory Load Multiresolution Data Structure Hierarchical Clustering View-dependent Level-of-detail Out-of-core Technology Small Block View-dependent Paging External Memory Out-of-core Visualization Error-controlled Lods Huge Point-sampled Model Partition-based Out-of-core Strategy Interactive Visualization Lod Organization Huge Point Model Experimental Result Commodity Graphic Platform Data Block Scheduling Algorithm General Pc Platform |
| Content Type | Text |
