「動跡剪輯」是將多個不同內容的影片片段，根據影片中特定物體移動的關係，剪接成新的影片，使得產生的新影片能維持動作連貫及流暢的特性。本論文提出一套方法能夠自動找尋不同影片間相似的剪輯點，作為「動跡剪輯」的參考。此方法之重點在於建立影片的時空資訊，作為找尋剪輯點的依據。建立影片時空資訊的過程中，我們先將影片依偵測出的鏡頭轉換點分割成不同的影片片段，再將影片片段中前景物件的位置、大小與動作等資訊分離而成影片物件平面，並結合影片片段中的背景動作資訊與影片物件平面資訊，成為該影片片段之時空資訊，從而進行剪輯點之找尋與比對，擇其最佳點進行剪輯。 運用影片時空資訊於找尋影片間之剪輯點時，是以影片物件平面作為搜尋單位，此方式有助於提升結果的正確性，同時也提供了搜尋時的靈活度。 / With the rapid increasing of the multimedia applications in modern commercial and movie business, it becomes more desirable to have efficient video editing tools. However, conventional video editing requires too many manual interventions that reduce productivities as well as opportunities in better performance. In this thesis, we propose a MOtion-based Video Editing (MOVE) mechanism that can automatically select the most similar or suitable transition points from a given set of raw videos. A given video can be divided into a set of video clips using a shot detection algorithm. For each video clip, we provide an algorithm that can separate the global motions as well as the local motions using the principles of video object plane and accumulated difference. We introduce the concept of spatio-temporal information, a condensed information that associated with a video clip. We can use this information in finding a good video editing point. Since the spatio-temporal information is a concise representation of a video clip, searching in this domain will reduce the complexity of the problem and achieve better performance. We implemented our mechanism with successful experiments.