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研究生： 唐昌宇
Tang, Chang-Yu
論文名稱： 針對蒙地卡羅路徑追蹤鏡面反射之路徑重複使用方法
A Path Reuse Method for Specular Surface Reflection in Monte Carlo Path Tracing
指導教授： 張鈞法
Chang, Chun-Fa
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： 英文
論文頁數： 33
中文關鍵詞： 路經追蹤 、全域照明 、蒙地卡羅方法
英文關鍵詞： path tracing, global illumination, Monte Carlo integration
DOI URL： https://doi.org/10.6345/NTNU202203628
論文種類： 學術論文
相關次數： 點閱：136  下載：10 
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    • 物理性質影像生成致力於產生逼真的影像，此技術被廣泛運用在許多產業之中，例如：電影產業中的電腦特效、建築與設計業中的3D模型預視；當然，還有電玩產業中的3D畫面。
    光線的資訊在現實世界中是無限的，所以我們必須透過採樣的方式來進行估測。處理全域照明（Global Illumination）的方法，對於產生的影像是否看起來真實佔了很重要的腳色，不同的採樣方法會對場景的呈現產生不同的結果。雙向路徑追蹤（Bidirectional Path Tracing）是基於蒙地卡羅路徑追蹤（Monte Carlo Path Tracing）的許多方法之一，為一種對於場景運算可以快速收斂的方法；然而，因為先天上的限制，此方法無法處理某些特定狀況，例如：路徑有鏡面至粗糙面又再到鏡面（specular-diffuse-specular）的情況，會影響產出影像的品質。在此篇論文中，我們提出了一個基於雙向路徑追蹤方法，藉由路徑重複使用來處理此狀況的折衷對策。

    Physically based image synthesis aims to render realistic images. It is widely used in many industries, e.g., Computer-generated imagery (CGI) in the movie industry, 3D models preview in the architecture and the design industry, and of course, 3D scenes in the computer gaming industry.
    In the real world, the information of light is infinite; therefore, we must do sampling to estimate it. How to deal with the global illumination effect plays an important role in whether the rendered image looks real or not. There are many sampling methods that reveal different features of the scene. Bidirectional path tracing, which is one of the Monte Carlo path tracing methods, is known for its quick convergence; however, due to innate limitation, it cannot handle some difficult cases, such as specular-diffuse-specular (SDS) paths. In this thesis, we introduce an alternative path reuse method while facing the SDS problem during the operation.

    List of Tables vii List of Figures viii 1 Introduction 1 1.1 Motivation 1 1.2 Contributions 2 1.3 Thesis Organization 3 2 Background 4 2.1 Measurement of Light Transport 4 2.1.1 Irradiance and Radiance 4 2.1.2 Bidirectional Reflectance Distribution Function 5 2.1.3 Rendering Equation 6 2.2 Monte Carlo Integration 6 2.2.1 Importance Sampling 8 2.2.2 Multiple Importance Sampling 8 2.3 Path Sampling Methods 10 2.3.1 Photon Mapping 10 2.3.2 Path Tracing 11 2.3.3 Bidirectional Path Tracing 12 2.4 Vertex Connection and Merging 13 3 Implementation 16 3.1 SmallVCM 16 3.2 Bidirectional Path Tracing Algorithm 17 3.2.1 Naïve Way 17 3.2.2 Implementation in Practice 17 3.2.3 Vertex Connection 18 3.3 The Specular-diffuse-specular Problem 20 3.4 A Path Reuse Method 21 4 Results 23 4.1 Test Scenes 23 4.2 Anylisis 24 4.2.1 Empty Cornell Box 24 4.2.2 Cornell Box with Spheres and Mirrors 25 4.3 Performance 27 5 Conclusions and Future Work 29 Bibliography 31

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