本研究提出一個應用於數位影片複製偵測之空間域與時間域特徵抽取機制，可應用於鑑別使用者上傳的影片之合法性。本研究方法是以影像內容的特徵為檢索基礎，並且提出新的空間域(spatial)特徵值為索引的快速近似方法來抵抗影片失真的狀況與提高辨識性，最後再使用新的時間域(temporal)特徵值的快速相似匹配方法，來鑑別使用者上傳的影片之合法性。本系統架構是基於H.264/AVC壓縮域的影片來執行解碼，進而分析每一組GOP(Group of Picture)值，來進行切換鏡頭畫面(SCF)的偵測分析，再從這些SCF集合中獲取時間域的數位特徵值，緊接著繼續從這些SCF集合中篩選出一個或是數個具代表此部Video的key frame，再透過我們提出的一種新的空間域特徵值提取方法來得到空間域的數位特徵值，最後我們僅需將產出的空間域與時間域的數位特徵值，儲存進資料庫中，並不需要花費大量的儲存空間來儲存原版影片。日後若需要鑑別使用者上傳的影片之合法性時，僅需比較在影片資料庫的空間域與時間域的數位特徵值即可。
我們提出的植基於內容的影片複製偵測方法，是適用於線上大量影片的複製偵測，例如鑑別使用者上傳到YouTube伺服器的影片之合法性。經過實際測試，在資料庫為252小時的影片中，使用者上傳影片的一張key frame的執行匹配計算時間約0.016秒。我們使用了MUSCLE-VCD-2007[34]與YouTube上大量影片來當作影片資料庫，並且使用一些失真的相似影片(例如在影片中加入noise、亮度改變、對比度改變、frame loss、frame insert、frame change、移位、旋轉、time shift)與不同影片來執行複製鑑別，實驗數據顯示了本機制是一個強健與高辨識性的系統，在對龐大的資料庫進行比較時，有高平均的查全率（Recall）與準確率（Precision），並能夠迅速地鑑別上傳的影片之合法性。

In this research, the techniques of spatial and temporal feature extraction are proposed for digital video copy detection. An efficient content-based video copy detection scheme based on the spatial and temporal feature extraction and matching is presented. The key-frames are selected to generate the spatial features, which are used as the anchor points for the temporal feature matching. The design considers the video coding structure so the efficiency and the compact size of feature database are the main contributions of the proposed framework. The experimental results show that the extracted feature can facilitate fast content matching for identifying the possible copies. The method should thus be feasible in matching contents in very large video databases.

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