Bidirectional Texture Function Modeling Using Optimized Reparameterization in the Lighting and Viewing Space
碩士 === 國立交通大學 === 多媒體工程研究所 === 97 === We present a new approach to model BTF data using multivariate SRBF kernels. More importantly, we propose a data-dependent parameterization method in which optimal parameterization in the lighting and viewing space that minimizes the modeling error is obtained....
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2008
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| Online Access: | http://ndltd.ncl.edu.tw/handle/06250985214224252178 |
| Summary: | 碩士 === 國立交通大學 === 多媒體工程研究所 === 97 === We present a new approach to model BTF data using multivariate SRBF kernels. More importantly, we propose a data-dependent parameterization method in which optimal parameterization in the lighting and viewing space that minimizes the modeling error is obtained. To speed up our BTF modeling computation and improve spatial coherence of acquired BTF model, we utilize a mipmap hierarchy in our BTF model, which can be nicely integrated with graphics hardware when rendering BTF data. Our experiments show that the optimal parameterization does provide better accuracy than a fixed parameterization such as the half-way parameterization. In addition, real-time rendering of BTF from novel viewing or lighting direction that is not recorded in the original BTF database can be achieved easily.
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