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Optimized mesh and texture multiplexing for progressive textured model transmission
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Source International Multimedia Conference archive
Proceedings of the 12th annual ACM international conference on Multimedia table of contents
New York, NY, USA
SESSION: Technical session 8: compression, streaming, and retrival of 3D objects table of contents
Pages: 676 - 683  
Year of Publication: 2004
ISBN:1-58113-893-8
Authors
Sheng Yang  University of Southern California, Los Angeles, California
Chao-Hua Lee  University of Southern California, Los Angeles, California
C.-C. Jay Kuo  University of Southern California, Los Angeles, California
Sponsors
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

An optimized scheme of multiplexing coded mesh and texture data to facilitate progressive transmission of 3D textured models is proposed in this work. The mesh and texture data of a 3D textured model are fed into their respective compression modules and represented by a series of levels of details. Then, for a given viewpoint, a rate-distortion surface can be generated based on the multiplexing of mesh and texture data in different details. The distortion is calculated by measuring the visual quality of rendered images. Furthermore, an optimal path over the rate-distortion surface is determined by the steepest descent algorithm. When the mesh and texture data streams are transmitted in a certain ratio along the optimal path, it is guaranteed that the rendered images have the best visual quality perceived from the given viewpoint. To deal with an arbitrary viewpoint, we propose a hierarchical sampling algorithm so that the optimal path can be interpolated from finite sampling points. Experimental results demonstrate that the proposed method can provide the best visual quality of a 3D textured model for any observation point at any bit rate.


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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Collaborative Colleagues:
Sheng Yang: colleagues
Chao-Hua Lee: colleagues
C.-C. Jay Kuo: colleagues