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研究生: 簡宏任
Chien, Hung-Jen
論文名稱: 動作瀏覽之運鏡設計
Camera Path Planning for Motion Overview
指導教授: 李同益
Lee, Tong-Yee
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2008
畢業學年度: 96
語文別: 中文
論文頁數: 74
中文關鍵詞: 視角挑選動畫動作捕捉器鏡頭
外文關鍵詞: Camera, View Selection, Animation, Motion Capture
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  • 在高效能電腦硬體已經相當普及的今天,不論是在遊戲、動畫或是三維環境中,電腦動畫的普遍化與高品質需求與日俱增。在現今的電腦動畫製作,Motion Capture取得的動畫扮演了一個非常重要的角色,應用這些真實的資料來修改創造出的電腦動畫,更能增加整個動畫的擬真度。而如何來提供一個清楚的瀏覽方式來觀看這些動作資料至今尚未被充分討論。

    我們研究的目的,就是要為一段未知的動畫設計其觀察路徑,提供動畫的瀏覽運鏡。我們設計了一個雙層搜尋的方法,用來規劃出瀏覽動作資料的鏡頭路徑,配合不同評估準則之間的比重調整,可以做出各種不同風格的運鏡結果。我們考慮到與動作有關的條件以及場景遮蔽的情況,並且強調鏡頭的穩定,並且可以達到即時的運算。

    Nowadays, the high performance hardware has been quite popular. The high-quality motions have been universal in computer games, animations or the 3D environment. The motion capture data has gained a leading role in the ways to get the virtual motions. Thus, We modify the real data to create the animations which are more realistic. Many of these applications require the creation of expressive overview video clips capturing the human motion. However sufficient attention has not been given to this problem.

    In this paper, we present a technique that generates a stable camera path for Mocap data. We consider having relations with motion and the occlusion of the scenes. We use a two-layer search algorithm to find suitable candidate and to select with prediction.

    中文摘要 I ABSTRACT II 誌 謝 III 目 錄 IV 圖目錄 VII 表格目錄 X 第1章 導論 1 1.1 研究動機與目的 1 1.2 研究內容與流程 4 1.3 主要研究貢獻 7 第2章 相關研究 9 2.1 靜態物件的視角評估 9 2.2 鏡頭路徑規畫 13 第3章 主要架構與演算法 20 3.1 視角評估 20 3.1.1 問題描述與討論 20 3.1.2 評估準則-標準視角 21 3.1.3 評估準則-最大投影量 24 3.1.4 評估準則-觀察距離 25 3.1.5 評估準則-自我遮蔽 26 3.1.6 評估準則-場景遮蔽 28 3.1.7 評估準則-使用者定義 34 3.1.8 最適當點搜尋 35 3.1.9 速度限制 36 3.2 研究觀察 39 3.2.1 觀察一 39 3.2.2 觀察二 40 3.2.3 觀察三 40 3.2.4 觀察四 41 3.3 路徑規畫 43 3.3.1 空間層的搜尋 43 3.3.2 畫格層的搜尋 46 3.3.3 多重攝影機 50 3.3.4 特別效果 52 第4章 結果與比較 54 4.1 結果路徑評估準則 54 4.2 平滑化與否的比較 55 4.3 與其他結果做比較 57 4.4 我們的結果 58 4.5 場景遮蔽的影響 61 4.6 使用者定義條件的影響 62 4.7 多重攝影機 64 4.8 實驗數據 66 4.9 問卷調查 67 第5章 結論與未來展望 69 5.1 結論 69 5.2 未來展望 69 5.3 方法限制 70 參考文獻 72

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