在有錯誤傾向的環境中，為了使以物件為基礎的影像能有較好的品質，形狀錯誤修復(SEC-Shape Error Concealment)是很重要的方法，最近Soares 和Pereira發表了一篇有效率的時間域形狀錯誤修復演算法，它結合單一階段移動補償(Global Motion Compensation)和局部再修復(Local Refinement)的方法來修復損壞區塊，其修復品質和以往已存在的方法有明顯的改善。基於輪廓配對之形態，本篇論文提出一種新穎的方法，只使用多階段移動補償的時間域形狀錯誤修復演算法，並將所產生的多組移動補償參數依使用輪廓點多寡排序，使各移動補償參數由粗到細作修復動作，和前述方法比較，在各種不同的錯誤樣式和錯誤率下，本方法對修復品質具有一些優勢。

In order to make the object–based video services reliable in error–prone environments with better quality, shape error concealment (SEC) is important. Recently, Soares and Pereira presented an efficient temporal SEC (TSEC) algorithm based on single–stage global motion compensation and local refinement; their proposed TSEC algorithm has significant quality improvement when compared to several existing algorithms. Based on the type of contour–pair, this thesis presents a novel adaptive and multistage–based
TSEC (AMTSEC) algorithm where the global motion parameters are sorted in order
to conceal errors in a coarse–to–fine way. Experimental results show that without local refinement, our proposed AMTSEC algorithm is some superior to the recently published TSEC algorithm in terms of the average video quality over different error patterns and loss rates.

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