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研究生: 賴威豪
Lai, Wei-Hao
論文名稱: 光線追蹤應用程式介面整合OpenGL程式設計
Ray Tracing API Integration for OpenGL Applications
指導教授: 張鈞法
學位類別: 碩士
Master
系所名稱: 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2016
畢業學年度: 104
語文別: 中文
論文頁數: 32
中文關鍵詞: 三維圖學光線追蹤遊戲引擎OpenCL
英文關鍵詞: 3D rendering, ray tracing, game engine, physically based rendering
DOI URL: https://doi.org/10.6345/NTNU202204398
論文種類: 學術論文
相關次數: 點閱:89下載:13
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  • 光線追蹤(ray tracing)是電腦圖學中一種重要的rendering技術,藉由模擬運算光的折射、反射…等光學現象來產生高品質畫面,但需要大量的運算與時間來滿足,因此在以前的硬體設備上想要達成即時(real-time)的效果幾乎不可能辦到。現今的GPGPU硬體設計架構使得GPU可被用來做自定義的平行化計算,因此許多學者提出運用CUDA或OpenCL實作光線追蹤或路徑追蹤(path tracing)…等physically based rendering的方法,期望藉由GPU高效率的平行計算使光線追蹤的效能大幅度提升。然而以光線追蹤方法仍難以受到主流遊戲開發業者採用,因為市場上的產品大部分都以光柵化(rasterization) rendering的設計為主,不容易在短期內發生改變,因此本篇論文想介紹一套類似於OpenGL API的整合設計,而底層rendering置換為光線追蹤或路徑追蹤…等physically based rendering的方法,幫助開發者使用現有的OpenGL應用程式原始碼並透過少許的修改就能獲得光線追蹤相關演算法rendering的畫面以及其帶來的好處。

    Ray tracing is one of the most important rendering technique in computer graphics. By means of simulating reflection and refraction of light, it generates an image with more photorealism than scanline rendering techniques. But the high computational cost of ray tracing is one of the algorithm main disadvantages. In recently years, the computing power of GPU has increased gradually, and the GPGPU applications model is more popular now. There are many scholars who introduce some physically based rendering methods with CUDA or OpenCL, in order to improve the image quality and increase rendering speeds. Nevertheless, there's no way ray tracing can be accepted by game development industry in the near future, because the design of the most products is based on rasterization rendering. In this research we introduce a ray tracing API integration for OpenGL applications, and we replace OpenGL rendering technique with ray tracing or other physically based rendering methods. So we can have advantages of ray tracing rendering technique by modifying few source codes.

    摘要 I ABSTRACT II 誌謝 III 目錄 IV 圖目錄 VI 表目錄 VI 第一章 緒論 1 第一節 研究背景 1 第二節 研究目的 1 第三節 論文架構 2 第二章 文獻探討 3 第一節 POWERVR OPENRL™ 3 第二節 NVIDIA OPTIX™ 5 第三節 MESA 3D 6 第四節 PBRT 7 第五節 OPENCL™ 7 Kernels and the OpenCL Execution Model 8 Memory Model 9 第三章 系統實作 10 第一節 整合系統概述 10 支援何種版本OpenGL以及功能 11 系統流程架構 12 第二節 API整合和擷取 14 The matrix manipulation functions 15 Client-side vertex arrays 17 Fixed-function lighting 18 OpenGL固定功能支援以及前置準備 19 第四章 光線追蹤 20 第一節 演算法概述 20 第二節 實作細節 20 計算交點測試 21 光照模型 22 場景加速結構 22 第五章 實驗與結果分析 23 實驗環境與場景資訊 23 驗證擷取功能 24 Cornell Box場景 24 額外擴充功能—反射 25 場景特性與效能測試 26 第六章 結論與未來方向 29 附錄A 30 圖片引用來源 31 參考文獻 32

    [1] Imagination Technologies, OpenRL SDK - Imagination Community. Available: https://community.imgtec.com/developers/powervr/openrl-sdk/

    [2] NVIDIA® OptiX™ Ray Tracing Engine | NVIDIA Developer. Available: https://developer.nvidia.com/optix

    [3] B. Paul. The Mesa 3D Graphics Library. Available: http://www.mesa3d.org/

    [4] M. Pharr and G. Humphreys, Physically based rendering: From theory to implementation: Morgan Kaufmann, 2004.

    [5] Khronos Group, OpenCL - The open standard for parallel programming of heterogeneous systems. Available: https://www.khronos.org/opencl/

    [6] B. Gaster, L. Howes, D. R. Kaeli, P. Mistry, and D. Schaa, Heterogeneous Computing with OpenCL: Revised OpenCL 1: Newnes, 2012.

    [7] Khronos Group, OpenGL - The Industry Standard for High Performance Graphics. Available: https://www.opengl.org/registry/

    [8] T. Whitted, "An improved illumination model for shaded display," presented at the Proceedings of the 6th annual conference on Computer graphics and interactive techniques, Chicago, Illinois, USA, 1979.

    [9] T. Möller and B. Trumbore, "Fast, minimum storage ray/triangle intersection," presented at the ACM SIGGRAPH 2005 Courses, Los Angeles, California, 2005.

    [10] B. T. Phong, "Illumination for computer generated pictures," Commun. ACM, vol. 18, pp. 311-317, 1975.

    [11] Z. Wu, F. Zhao, and X. Liu, "SAH KD-tree construction on GPU," presented at the Proceedings of the ACM SIGGRAPH Symposium on High Performance Graphics, Vancouver, British Columbia, Canada, 2011.

    [12] A. Keller, S. Premoze, and M. Raab, "Advanced (quasi) Monte Carlo methods for image synthesis," in ACM SIGGRAPH 2012 Courses, 2012, p. 21.

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