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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/48229
標題: | 擴增關鍵頁框 Augmented Keyframe |
作者: | Gwo-Cheng Chao 趙國成 |
指導教授: | 鄭士康 |
關鍵字: | 關鍵頁框,影片摘要,監控影片,擴增關鍵頁框, Keyframe,video summarization,surveillance video,augmented keyframe, |
出版年 : | 2011 |
學位: | 博士 |
摘要: | 近年來由於安全監控產業蓬勃發展,使得目前一般監控設備都已朝數位化方式演進,但是這類儲存檔案通常極為冗長,譬如包含一整天、一星期甚至數個月的內容。因此想在大量的檔案中,有效地進行影像的搜尋與瀏覽,就需要一些視覺化索引工具來幫忙。在監控應用中關鍵頁框(keyframe)是較常被用來進行監控影片檔案的瀏覽與檢索的視覺化索引工具,然而一般傳統的關鍵頁框的產生方式,大部份還是取用監控影片內的頁框 (frame)來當成關鍵頁框,而以這種形式呈現的關鍵頁框,所包含的監控影片內容資訊經常不足,並且無法讓使用者清楚了解整段監控影片發生的事情,此外傳統的關鍵頁框的產生方式,也通常需要產生大量的關鍵頁框才能描述一段影片的內容,因此是很沒有效率的。
本論文提出一個新型態的關鍵頁框,我們稱為擴增關鍵頁框(augmented keyframe),這個擴增關鍵頁框是充滿意義與緊實的,其內容包含了一段由靜態攝影機所拍攝的監控影片,所取出之移動物體的代表性影像、影片重要內容(如人臉,車牌等)、移動物體的移動資訊(包含:軌跡資訊與簡單的移動情況資訊等),與一些標籤資訊等。這個新的技術主要由兩個不同階段的步驟所組成,分別為內容擷取(content extraction)與內容合成(content synthesis)。本論文創新之處在於我們提出兩個不同的內容合成(content synthesis)方法,分別基於2維與3維資訊來產生我們所提出的擴增關鍵頁框(augmented keyframe);而透過比較與使用者調查等實驗,我們可以證實擴增關鍵頁框可以比傳統的關鍵頁框方法,產生更容易被理解與有意義的關鍵頁框,並且可以收集到較好的使用者回應。 The surveillance industry grows vigorously in recent years, and the monitoring equipments have been mostly digitalized. However, the recorded video files are usually very long, including contents for activities all day long or even several months. For retrieving and browsing the desired video file from the database efficiently, the user needs some visual indices. In surveillance applications, the keyframe approach is more popular in browsing and retrieval on video. However, traditional keyframe extracting methods select video frames as keyframes directly from the input video, and the information in these selected video frames is scattered and does not easily let the users perceive how the events happened in the original video. In addition, they will need to generate a lot of keyframes to express events recorded in the video, which is not very efficient. In this thesis, we propose a new type of keyframe (called an “augmented keyframe”) that is a more meaningful and compact keyframe, augmented with representative objects, important contents (human faces, license plates, etc.), motion information (including trajectories and simple movement situations), and some marks of the moving objects extracted from a surveillance video clip captured by a static camera. This new technique consists of two major phases: content extraction and content synthesis. The innovation is that we propose two different content synthesis approaches (based on the 2D and the 3D information, respectively) to generate the augmented keyframe. In addition, we show through the comparison and the user study in our experiments that the augmented keyframe can generate more comprehensible and meaningful keyframes and collect better user feedback than traditional keyframe approaches. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/48229 |
全文授權: | 有償授權 |
顯示於系所單位: | 資訊網路與多媒體研究所 |
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ntu-100-1.pdf 目前未授權公開取用 | 1.79 MB | Adobe PDF |
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