有越來越多關於視訊資料查詢的研究，去描述影片中的物件的屬性變化與移動。然而，這樣的描述方式並不適用於描述一個複雜的「故事」，好比一部電影情節。為了要讓查詢可以使用這些故事和事件當成條件，我們提供了一個語意化的查詢系統。在這個系統裡面，我們使用一個階層化的知識模型去描述現實世界中各項事物間的關係。這個模型具有彈性，可以用不同的形式去定義來配合不同場合的需要。然後我們提供了一個語意化的視訊查詢語言，使用者可以定義名詞、動詞和關係等等類別的變數去組成一個可以表達豐富含意的查詢。藉由前面提到的知識模型，系統可以對出現於查詢中的變數進行推理，以判斷資料庫中某個物件是否在語意上與這些變數符合。最後，我們還提出了一個衡量語意相似程度的方法，來達到容錯查詢的能力。

More and more researches on the video retrieval express attribute changes and movements of the objects appearing in a video document. However, these expressions are hard to describe a complex “story” of a video document such as a movie. In order to query a video document according to the events and stories happening in it, a semantic video retrieval system is proposed. In this system, we use a hierarchical knowledge model to explain the relationships between each thing in the real world. This model is flexible and can be defined for different applications. Then we provide a video query language having many semantic characteristics. Users can use the terms of Noun, Verb and Relation to make a query that represents rich and complex semantic meanings. By cooperating with the proposed knowledge model, the retrieval system is able to do some inferences on the terms appearing in a query, and determine whether a candidate in the video database semantically matches them. Finally, a semantic similarity measurement is proposed to achieve the fault-tolerant query.

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