隨著數位時代的來臨，聲音、影像等各式各樣的資訊不僅能以更有效率、更加方便的形式被儲存，同樣也造成大量的影音資訊累積氾濫的問題。由於完全以人工方式對大量影片內容作註解需仰賴極大人力，且難以針對影片中每個段落定下客觀而詳盡的文字描述，而造成傳統上以文字查詢的方式，無法滿足影片內容搜尋上的需求。為了能在大量的數位影片中針對視訊內容查詢出特定影片段落，我們需藉由電腦事先對數位影片做自動而快速的分鏡偵測，再針對各個分割出來的鏡頭取出視訊特徵，再分就不同特徵以自動或半自動的方式加上客觀註解，並經整理分類存放於資料庫中，當使用者希望查詢某種影片內容時，可以直接透過電腦對此一建構過的資料庫做快速而有效比對，達到真正對影片內容查詢與瀏覽的目的。 有鑑於此，本論文主要提出兩項以視訊內容為基礎，應用於MPEG影片之視訊檢索技術。首先，我們針對慢換景(gradual transition)中最常被使用，也最難被現有技術正確判斷出來的溶解特效作研究。利用每個像素位置的亮度變化，統計所有在時間軸上符合線性變化特性的像素數量百分比，並與藉由累加二項式分配所預估出的門檻值比較，已達到明顯辨識出溶解式(dissolve)慢換景的目的。再對影片畫面序列做重新取樣，使偵測的正確率不受溶解特效的時間長短而降低。我們也可應用同一原理來偵測淡入(fade-in)、淡出(fade-out)形式的慢換景。理論與實驗結果都證實，我們的方法不僅快速有效，更能達到其他同類型研究所難達到的低錯誤率，真正有效降低因影片中的物體、攝影機運動所造成的大量誤判情況發生。 其次，我們提出了以應用層面最廣的MPEG影片為對象，藉由分析整理其內含之運動向量資訊，自動生成影片中移動物體的軌跡資訊，使我們在方法上有著下列優點：<1>直接應用現成已有的運動向量資訊，使註解時間更為快速。<2>影片中有多個移動物體之情況亦適用。<3>不受限於靜止裝設之攝影機所拍攝的影片。另一方面，我們亦發展了快速的軌跡比對策略，透過不同以往的座標表示法，使多數非相似軌跡僅須比對少數控制點就能加以排除，大幅加速檢索效率。 Gradual shot change detection is one of the most important research issues in the field of video indexing/retrieval. Among the numerous types of gradual transitions, the dissolve-type gradual transition is considered the most common one, but it is also the most difficult one to detect. In most of the existing dissolve detection algorithms, the false/miss detection problem caused by motion is very serious. In this thesis, we present a novel dissolve-type transition detection algorithm that can correctly distinguish dissolves from disturbance caused by motion. We carefully model a dissolve based on its nature and then use the model to filter out possible confusion caused by the effect of motion. Furthermore, we propose the use of motion vectors embedded in MPEG bitstreams to generate so-called “motion flows”, which are applied to perform quick video retrieval. By using the motion vectors directly, we do not need to consider the shape of a moving object and its corresponding trajectory. Instead, we simply “link” the local motion vectors across consecutive video frames to form motion flows, which are then annotated and stored in a video database. In the video retrieval phase, we propose a new matching strategy to execute the video retrieval task. Motions that do not belong to the mainstream motion flows are filtered out by our proposed algorithm. The retrieval process can be triggered by query-by-sketch (QBS) or query-by-example (QBE). The experiment results show that our method is indeed efficient and accurate in the video retrieval process.
