臺灣博碩士論文加值系統

傳統中國水墨人物畫中，有時因為衣服材質的不同而表現出衣物輕柔或厚重的感覺，也有時是為了特別呈現出衣褶繁複的模樣，因而發展出了眾多的描法。對於同一個人物，若要從另一不同角度作畫，必須整張圖重畫，而且在畫作完成前，我們無法事先預知最後展現結果為何。一旦作畫過程出現失誤，便要重新再畫一次，相當耗時。在本篇論文中，我們提出一個依據三維人物模型來自動產生水墨人物畫描法。對同一個立體人物模型，我們可畫出不同的描法，也可以產生不同觀看角度的水墨人物畫。對使用者而言不需對水墨人物畫的描法很熟練，就可以在短時間內產生出所需要的一張畫。

In traditional Chinese Ink figure paintings, in order to represent the soft or heavy materials of clothes, or sometimes we want to show that the clothes are full of creases, various Miao skills were developed. If we want to paint the same figure in another view, we should start over and draw again. Besides, we do not know what the final results looked like before the painting is finished. Once a mistake was made, we have to paint again until it is desired that wastes so much time. In this thesis, we propose a method to generate the Chinese Ink Figure Paintings automatically according to three-dimensional models. We can produce figures of the same three-dimensional model in different Miao skill from different views. In this way, painters can create good-looking figure paintings easily without understanding any Chinese painting skills. Moreover, painters may try different styles in short time to get various effects of the Chinese Ink figure paintings.

CHAPTER 1 INTRODUCTION1
1.1 MOTIVATION1
1.2 SYSTEM OVERVIEW2
1.3 THESIS ORGANIZATION3
CHAPTER 2 RELATED WORKS4
CHAPTER 3 OUTLINE EXTRACTION8
3.1 MODEL PREPROCESSING9
3.2 OUTLINE EXTRACTION OF THE HEAD MODEL9
3.3 OUTLINE EXTRACTION OF THE BODY MODEL12
CHAPTER 4 OLIVE MIAO15
4.1 ABOUT OLIVE MIAO15
4.2 STROKE OF OLIVE MIAO17
4.2.1 Properties of Stroke17
4.2.2 Decide Olive parts of Feature Pixels18
4.2.3 Length of Strokes22
4.3 PAINTING ALGORITHM25
4.3.1 Brush Model25
4.3.2 Ink Blending Mechanism29
4.3.3 Reduction of the Over-thick Part30
CHAPTER 5 NAIL-TIPPED-MOUSE-TAILED MIAO32
5.1 ABOUT NAIL-TIPPED-MOUSE-TAILED MIAO32
5.2 STROKE OF NAIL-TIPPED-MOUSE-TAILED MIAO33
5.2.1 Properties of Nail-Tipped-Mouse-Tailed Miao33
5.2.2 Decide Strokes for Featured Pixels34
5.3 PAINTING ALGORITHM37
5.3.1 The Tip Part37
5.3.2 The Middle Part38
5.3.3 The Tail Part39
CHAPTER 6 EXPERIMENTAL RESULTS40
CHAPTER 7 CONCLUSIONS AND FUTURE WORKS47
REFERENCE 49

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