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研究生： 陳宏光
Hung-Kuang Chen
論文名稱： 三維物件的高效能大型多邊形網格化簡方法之研究
A Study on the High-Performance Approaches to Large Polygonal Mesh Simplification of 3D Objects
指導教授： 林銘波
Ming-Bo Lin
范欽雄
Chin-Shyurng Fahn
口試委員: 楊熙年
Shi-Nian Yang
莊榮宏
Rong-Hung Juang
李宗南
Tzun-Nan Lee
李同益
Tony Tung-Yi Lee
鍾國亮
Kuo-Liang Chung
學位類別： 博士
Doctor
系所名稱： 電資學院 - 電子工程系
Department of Electronic and Computer Engineering
論文出版年： 2006
畢業學年度： 94
語文別： 英文
論文頁數： 107
中文關鍵詞： 三維物件 、多邊形網格 、大形多邊形網格 、多邊形網格化簡
外文關鍵詞： 3D object, polygonal mesh, large polygonal mesh, polygonal mesh simplification
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  •  上一筆

    • 由於為許多著色系統支援，多邊形網格已成為多年來三維物件的主流表示法。然而，這類表示法往往需要巨量的多邊形來表示高細節的物件。作為一個防止過度使用多邊形的相當有用的方法，多邊形簡化演算法的研究在近二十年來被密集的研究著.
    傳統的內核遞迴邊縮減式簡化演算法通常可產生相當高品質的簡化模型. 但是，這一類的演算卻具有相當低的執行效率及與輸入大小相關的大量記憶體需求。另一方面來說，外核格篩式演算法雖能有效率的處理大型多邊形網格的化簡，卻在使用低解析度網格時往往產生相當低品質的輸出。
    在本篇論文中，我將提出三種新的作法：第一種是能產生高品質輸出，低儲存體需求，高效能線性時間的演算法。其次是一個用來處理大量多邊形網格整合快取的外核系統。最後是一個可用來整合多種不同型式簡化演算法，並可同時允許內核、外核、混合型操作、及兩段式簡化的一個與儲體不相依的多邊形網格化簡系統。

    Owing to the support by most rendering systems, the polygonal mesh representation has been the dominant representation scheme of 3D objects for many years. However, to represent an object in high resolution, it usually requires enormous amount of polygons. Consequently, the polygonal mesh simplification as a very useful scheme to prevent from overly use of polygons was intensively studied.
    Traditional iterative-edge-collapse-based in-core simplification algorithms usually create very good quality approximations. Somehow, this class of algorithms has relatively low runtime efficiency and large main memory cost that is sensitive to its input mesh size. On the other hand, the out-of-core grid-based algorithms capable of dealing with very large meshes often create very low quality approximations at low resolution grids.
    In this dissertation, we will propose a linear-time high efficiency and low main memory cost simplification algorithm for high quality discrete LOD generations, a novel cache-based approach to dealing with large meshes, and a storage independent simplification system allowing in-core, out-of-core, hybrid operations, and multistage integration of simplification algorithms of various types.

    Chapter 1 Introduction 1 1.1 The Background 1 1.2 The Problem Statement 3 1.3 Motivations and Contributions 4 1.4 Dissertation Outline 6 Chapter 2 Terminology 7 2.1 Topological Notations 7 2.2 The Ring of a Vertex 7 2.3 The Quadric Error Metrics 8 2.4 The Replacement Selection Heap 9 2.5 The Cache Algorithms 11 Chapter 3 Related Work 13 3.1 The Simplification Schemes 13 3.1.1 Iterative contraction 13 3.1.2 Grid-based re-sampling 16 3.2 Related Algorithms 17 3.2.1 The in-core simplification algorithms 17 3.2.2 The simplification algorithms for large meshes 18 3.2.3 The multiphase approach 20 3.3 The Level-of-Detail Representations 20 3.3.1 Discrete LOD 21 3.3.2 Dynamic LOD 21 3.3.3 View-Dependent LOD 21 Chapter 4 A Linear Time Polygonal Mesh Simplification Algorithm 23 4.1 The Simplification Algorithm 24 4.1.1 The vertex ring construction stage 26 4.1.2 The simplification stage 27 4.1.3 The output stage 32 4.1.4 Time complexity analysis 32 4.2 Experimental Results 34 4.2.1 Memory costs 35 4.2.2 Runtime efficiency 36 4.2.3 Output quality 37 4.3 Discussions and Conclusions 38 Chapter 5 A Novel Cache-Based Approach to Large Mesh Simplification 46 5.1 Overview 46 5.2 The Simplification Layer 47 5.2.1 The input mesh and associated data structures 48 5.2.2 The construction of vertex rings 49 5.2.3 The computation stage 50 5.2.4 The contraction stage and the dependency control strategies 54 5.2.5 The output stage 58 5.3 The Cache Layer 59 5.4 Experimental Results 61 5.4.1 The memory costs and running times 62 5.4.2 The evaluation of output quality 64 5.5 Discussions and Conclusions 70 Chapter 6 The Storage Independent Simplification System 72 6.1 The System Overview 72 6.2 The Algorithm Layer 73 6.2.1 Algorithm I – a linear-time iterative edge collapse algorithm 74 6.2.2 Algorithm II – a uniform-grid vertex clustering algorithm 75 6.3 The Data Management Layer 76 6.3.1 The device independent primitives 77 6.3.2 The operation modes 77 6.3.3 The initialization flows 80 6.4 Experimental Results 81 6.4.1 Running times 81 6.4.2 The comparisons 82 6.5 Discussions and Conclusions 89 Chapter 7 Conclusion and Future Work 90 7.1 Conclusion 90 7.2 Future Work 91

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