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研究生:趙士賓
研究生(外文):Shih-Pin Chao
論文名稱:高層次人體動畫合成
論文名稱(外文):High-level Human Motion Synthesis
指導教授:楊熙年
指導教授(外文):Shi-Nine Yang
學位類別:博士
校院名稱:國立清華大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2005
畢業學年度:94
語文別:英文
論文頁數:80
中文關鍵詞:動畫技術由動作/影片資料產生之動畫鉸接式關節結構之動畫動畫系統動作捕捉與重置語言剖析與瞭解基於動力學之動畫合成動作捕捉與人體動畫模擬動作控制程序式建模
外文關鍵詞:animation techniquesanimation from motion/video dataanimation of articulated figuresanimation systemmotion capture and retargetinglanguage parsing and understandingdynamics-based animationmotion capture and human body simulationmotion controlprocedural modeling
相關次數:
  • 被引用被引用:1
  • 點閱點閱:298
  • 評分評分:
  • 下載下載:37
  • 收藏至我的研究室書目清單書目收藏:2
動作捕捉技術的普遍與流行於近幾年帶動了以動作樣版為素材的人體動作合成方法。但是許多已提出的方法僅僅以數學分析從動作樣版中採集低層次的動作素材進行合成,導致高層次的動作操控方式和這些方法提供的低層次動作素材無法直接銜接,而此一缺點限制了動作樣版為素材的動作合成法之更廣泛的應用。為了降低上述提及的高層次控制與動作合成間之隔閡,本論文對於高層次人體動作合成與操控提出一些可行的解決方法。本文提出的方法主要在強調基於文字的動作合成和基於動作質地之風格合成。首先在基於文字的動作合成上,我們運用文字分析法採集一組具有語意與文字對應的基本動作,接著根據給予的基本動作文字提出一種半自動的動作標註法,於是下達的文字描述要轉成動畫便可經由串接合成一連串基本動作文字所對應的動作片段來達成。接著於風格合成上,我們以拉邦動作分析(LMA—Laban Movement Analysis)的動作質地做為基於質地的風格合成法之核心,主要是因為拉邦動作分析的勁道(Effort)已被廣泛運用於許多動作研究領域上,本篇論文提出一種動力學為基礎之勁道模擬器,能夠根據下達之勁道質地(Effort Qualities)去改變下達的動作捕捉資料之勁道。我們提出的勁道模擬器之基本概念是去建立勁道因子(Effort Factors, 如空間、輕重、時間與流動)和動力學參數間之對應關係(如力量、剛性、慣量、阻泥與重力等等),於是下達之勁道質地便能夠轉換為對應的動力學參數。換句話說,本文提出的模擬器不僅可以有效地模擬出給予的動作之細微資訊,並且能夠根據下達之勁道質地去改變給予的動作捕捉資料之勁道。此外,本文亦對限制條件滿足的問題提出解法,所以動作在經過我們的方法編修之後,還能夠保有原來動作的細微資訊與符合動力學的限制條件。
Recent advances in motion capture techniques facilitate the active research in example-based human motion synthesis. However, many proposed solutions only identify low-level motion elements which are derived from mathematic analysis of motion examples. These solutions provide no direct connection between high-level motion specification and low-level motion elements. This drawback limits the usefulness of example-based approaches. To alleviate the above mentioned gap, this study proposes some possible solutions to the high-level motion synthesis and control. The proposed solutions emphasize on the realization processes of text-based motion synthesis and quality-based style synthesis. For text-based solution, we use text analysis method to identify a set of meaningful basic motions. Then, an annotation method is introduced to automatically label motion data according to given basic motion texts. Therefore, a new motion with given textual description can be synthesized by concatenating motion clips of basic motion texts in the description. As for style synthesis, we use motion qualities in Laban Movement Analysis (LMA) to construct our quality-based style synthesis kernel. As the Effort component of LMA has been used by many movement related fields, we present a dynamics-based Effort simulator so that a given motion capture data can be modified according to specified Effort qualities. The basic idea of our Effort simulator is to establish relations between Effort factors such as Space, Weight, Time, and Flow, and their corresponding dynamics parameters such as force, stiffness, inertia, damping, gravity, and etc. Then, a specified Effort quality can be realized by giving proper values of corresponding dynamics parameters. In other words, the proposed simulator not only can mimic the given motion effectively, but also provides control capability for varying given movement according to specified Effort qualities. Moreover, we also propose solutions to constraint satisfiable problem so that motion details and dynamics constraints of the original motion capture data can be preserved after modification.
TABLE OF CONTENTS
CHINESE ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . ii
ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
ACKNOWLEDGEMENTS . . . . . . . . . . . . . . . . . . . . . . v
LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . viii
LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . ix
I INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . 1
II HUMAN MOTION SYNTHESIS WITH HIGH-LEVEL CONTROL
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1 Text-based Motion Generation . . . . . . . . . . . . . . . . . 4
2.2 Style-based Qualitative Variations . . . . . . . . . . . . . . . 5
2.3 Example-based Motion Synthesis with High-level Control . . 6
III MOTION MANUAL-BASED MOTION SYNTHESIS . . 7
3.1 Construction of Motion Index Table . . . . . . . . . . . . . . 11
3.2 BMT-normal Form Directory . . . . . . . . . . . . . . . . . . 14
3.2.1 Motion Annotation . . . . . . . . . . . . . . . . . . . 17
3.3 High-level Motion Control . . . . . . . . . . . . . . . . . . . 20
3.4 Motion Synthesis by Path Finding Algorithm . . . . . . . . . 22
3.4.1 Path Finding . . . . . . . . . . . . . . . . . . . . . . . 23
3.5 Synthesized Examples and Discussions . . . . . . . . . . . . . 25
3.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
IV QUALITY-BASED STYLE SYNTHESIS . . . . . . . . . . . 30
4.1 Effort Qualities and Simulator Framework . . . . . . . . . . 32
4.2 Effort Simulator . . . . . . . . . . . . . . . . . . . . . . . . . 33
4.2.1 Dynamics-based Motion Capture-driven Controller . . 35
4.2.2 Proposed Effort-Controller . . . . . . . . . . . . . . 36
4.3 Dynamics Parameters and Effort Qualities . . . . . . . . . . 40
4.3.1 Indirect and External Force . . . . . . . . . . . . . . 41
4.3.2 Direct and External Force . . . . . . . . . . . . . . . 42
4.3.3 Light and Stiffness and Anti-Gravity . . . . . . . . . 43
4.3.4 Strong and Stiffness . . . . . . . . . . . . . . . . . . 45
4.3.5 Sustained and Rotational Inertia . . . . . . . . . . . 46
4.3.6 Sudden and Rotational Inertia . . . . . . . . . . . . 46
4.3.7 Free and Damping . . . . . . . . . . . . . . . . . . . 47
4.3.8 Bound and Damping and Anti-Gravity . . . . . . . . 49
4.3.9 Summary of Effort Values and Dynamics Parameters 50
4.4 Synthesized Examples and Discussions . . . . . . . . . . . . . 50
4.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
V CONSTRAINT SATISFACTION . . . . . . . . . . . . . . . . 67
5.1 Balance Constraint Satisfaction . . . . . . . . . . . . . . . . . 70
5.2 Original Constraint Satisfaction . . . . . . . . . . . . . . . . 71
5.3 Two-Step Constraint Satisfaction . . . . . . . . . . . . . . . . 72
VI CONCLUSION . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
vii

LIST OF TABLES
1 Relationships between Effort qualities and Dynamics parameters.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

LIST OF FIGURES
1 Framework of the proposed motion manual-based motion synthesis.
(1) Motion database; (2) BMT-normal form directory;
(3) User interfaces; (4) Motion synthesis. . . . . . . . . . . . . 8
2 Features of a single limb vector. . . . . . . . . . . . . . . . . . 12
3 Indexing of a single arm. . . . . . . . . . . . . . . . . . . . . . 14
4 Normal form structure. . . . . . . . . . . . . . . . . . . . . . . 16
5 Search similar Moclip. . . . . . . . . . . . . . . . . . . . . . . 18
6 (a) Given annotated example; (b)–(e) Retrived similar Moclips. 19
7 TCC motion hierarchy. . . . . . . . . . . . . . . . . . . . . . . 21
8 Motion synthesis by path finding. . . . . . . . . . . . . . . . . 23
9 Example of images to animation. . . . . . . . . . . . . . . . . 27
10 Example of text description to animation. . . . . . . . . . . . 28
11 Framework of Effort simulator. . . . . . . . . . . . . . . . . . 34
12 User interface of Effort simulator. . . . . . . . . . . . . . . . 35
13 Samples of the neutral cyclic motion. . . . . . . . . . . . . . . 38
14 The influences of high stiffness on PD, FF, and Effort controllers. 38
15 The deviation of the end-effector trajectory. . . . . . . . . . . 42
16 The alignment of the end-effector trajectory. . . . . . . . . . . 44
17 Ghost comparisons from the simulated Space motion exmples. 53
18 Path curvatures (left) and corner curvatures (right) of the performed
Space motion examples. . . . . . . . . . . . . . . . . . 54
19 Path curvatures (left) and corner curvatures (right) of the simulated
Space motion examples. . . . . . . . . . . . . . . . . . 55
20 Ghost comparisons from the simulated Weight motion examples. 57
21 Path curvatures (left) and corner curvatures (right) of the performed
Weight motion examples. . . . . . . . . . . . . . . . . 58
22 Path curvatures (left) and corner curvatures (right) of the simulated
Weight motion examples. . . . . . . . . . . . . . . . . 59
23 Ghost comparisons from the simulated Flow motion examples. 60
24 PAD comparisons between the performed and the simulated
Flow motion examples. . . . . . . . . . . . . . . . . . . . . . . 61
25 Ghost comparisons from the simulated Time motion examples. 64
26 Acceleration derivatives of the performed (left) and the simulated
(right) Time motion examples. . . . . . . . . . . . . . 65
27 The comparision between synthesized human motions with balance
and without balance constraints. (a) Balance; (b) No balance.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
28 The violations of the original constraint from the motion capture
data. (a) The original biped constraint; (b) The foot penetrating
the floor; (c) The feet being suspended in midair. . . 70
29 Two-step constraint satisfaction. . . . . . . . . . . . . . . . . . 73
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