近年來在動畫製作的過程中對於動作的合成常利用到動作擷取器(Motion Capture)，但在動作擷取之後，若演員的身材比例與虛擬角色的體型有所出入，則在虛擬角色上直接套用所擷取之動作將有所失真。最常見的情形就是滑步、浮空、陷入地面等動作定位的問題。本篇論文之目的在於研究失真的原因並提出調整動作資訊的方法，以解決肢體定位錯誤與修正動作失真的問題，使得任何體型演員所擷取之動作均能適用於不同身材比例的虛擬角色上。
對於定位的問題，我們可由原始動作資料中獲得原骨架各肢體的端點位置軌跡(End-effector trajectory)，以這些軌跡使用逆向運動學(Inverse Kinematics)的技術來逆推回不同體型骨架之關節角度，進而重建其動作資訊。但是從原始骨架動作中獲得的各肢體端點位置，並不適合於不同體型骨架的端點位置，單純以這些端點位置進行動作重置雖然可達到正確的定位，可是關節的角度常需要大幅改變才能達到標的位置，以致產生畸形的動作。我們依不同體型之骨架修正目標端點位置，使重置後的動作和原始的動作更為相像，且動作也不會發生定位的錯誤情況。此外更因為傳統的逆向運動學所計算出的關節角度並非唯一，所以我們利用動作擷取器所獲得連續密集資訊的特性，使得逆向運動學得到最接近原始動作姿勢的關節角度，而重置後的動作將儘可能的滿足所設定之限制條件。此外，因為取樣密集，所以每格動作之間的差距都很小，雖然資料是離散的，但極短時間片段中可視為近似於連續性的，所以重置後仍會保持平順的動作。

In this paper, we extend per-frame inverse kinematics technique for retargeting motion, and propose end-effector correction method to increase the similarity of the retargeted motion.
Per-frame inverse kinematics uses end-effector of original skeleton in the motion to obtain joint angles of target skeleton. Retargeting by the trajectories of source end-effector can guide limbs to reach validly position, and preserve important aspects of the original motion. However, the retargeted motion may not achieve required quality of similarity. In this study we propose end-effector correcting mechanisms. Base on these mechanisms, two retargeting algorithms, which can perform similar motion without violating the given constraints are introduced. Moreover, empirical tests are given to demonstrate the effectiveness and efficiency of our algorithms.

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