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Huge texture mapping for real-time visualization of large-scale terrain
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Source Virtual Reality Software and Technology archive
Proceedings of the ACM symposium on Virtual reality software and technology table of contents
Hong Kong
SESSION: Session 2B: real-time interactions and rendering (short papers) table of contents
Pages: 154 - 157  
Year of Publication: 2004
ISBN:1-58113-907-1
Authors
Wei Hua  Zhejiang University, Hangzhou, P.R. China
Huaisheng Zhang  Zhejiang University, Hangzhou, P.R. China
Yanqing Lu  Zhejiang University, Hangzhou, P.R. China
Hujun Bao  Zhejiang University, Hangzhou, P.R. China
Qunsheng Peng  Zhejiang University, Hangzhou, P.R. China
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
Publisher
ACM  New York, NY, USA
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ABSTRACT

Texture mapping greatly influences the performance of visualization in many 3D applications. Sometimes the texture data is so large that it has to be stored in slower external storage, rather than fast texture memory or host memory. In these circumstances, texture mapping becomes the performance bottleneck. In this paper, we present a compact multiresolution model, Texture Mipmap Quadtree (TMQ), to represent large-scale textures. It facilitates fast loading and pre-filtering of textures from slower external storage. Integrating continuous LOD model of terrain geometry, we present a criterion to select proper textures from TMQ according to viewing parameters during rendering stage. By exploiting temporal coherence, a dynamic texture management scheme is devised based on two-level cache hierarchy to further increase the performance of texture mapping.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Linde, Y., Buzo, A., and Gray. R. M. An Algorithm for Vector Quantizer Design. IEEE Transactions on Communications, 28(1):84--95, 1980.
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Collaborative Colleagues:
Wei Hua: colleagues
Huaisheng Zhang: colleagues
Yanqing Lu: colleagues
Hujun Bao: colleagues
Qunsheng Peng: colleagues