臺灣博碩士論文加值系統

多光譜雙向紋理函數(Multi-Spectral Bidirectional Texture Functions)是用來描述複雜物體外觀的一種方法，同時也能在不同的光照環境之下重現正確的顏色，但是資料量龐大的多光譜雙向紋理函數如果未經壓縮將難以有效地運用於描繪三維場景。本篇論文將基於圖形處理單元之張量近似法(GPU-Based Tensor Approximation, GPU-Based TA)用於壓縮多光譜雙向紋理函數，並且提供在壓縮以及描繪程序上的實作細節。其中包含透過啟發式方法來決定多光譜雙向紋理函數的壓縮參數，以及為描繪多光譜雙向紋理函數所設計的即時繪圖演算法，用來增進壓縮與描繪的效能以及品質。除此之外，我們也透過實驗來證明GPU-Based TA對於多光譜雙向紋理函數而言是一個高效率的壓縮方法，同時也透過不同的程式設定來調教該方法在壓縮多光譜雙向紋理函數時的執行效能。

Multi-Spectral Bidirectional Texture Functions (MSBTFs) are designed for the accurate color reproduction of complex materials in virtual scenes with arbitrary illumination. However, rendering MSBTFs at interactive rates is challenging since the amount of datasets is huge. This thesis applies a GPU-based tensor approximation framework for compressing MSBTFs and discusses some practical details about compressing and rendering MSBTFs. We also present a heuristic method that decides suitable compression parameters for better offline performance and a novel technique for efficient rendering at runtime. Finally, we analyze the offline performance of the GPU-based framework with thorough experiments to prove its efficiency and find out appropriate configurations for compressing MSBTFs.

1. Introduction 1
2. Related Work 2
2.1 BTF Compression 2
2.2 Tensor Approximation 4
2.3 Spectral Rendering 5
3. Background 6
3.1 Notation 6
3.2 Tucker Decomposition 6
3.3 GPU-Based TA 7
4. Compression and Rendering of MSBTFs 8
4.1 Compressing MSBTFs 8
4.1.1 Determining Reduced Ranks 8
4.2 Rendering MSBTFs 10
5. Results 11
5.1 Cache-Aware Scheduling 13
5.2 Configurations of GPU-Based TA 13
6. Conclusions 15
References 18

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