本文選題：視頻內容分析 + MPEG-2�。� 參考：《北京工業(yè)大學》2016年碩士論文

【摘要】：視頻內容分析(Video Content Analysis,VCA)一直是多媒體領域最受關注的研究課題之一,經過多年的研究,取得了一定的研究進展,目前已廣泛應用于視頻近拷貝檢測、廣告投放以及視頻檢索等多個領域。視頻內容分析的關鍵部分在于如何提取視頻特征,從而對視頻內容進行有效、全面的描述。近年來,圖像內容分析技術、圖像局部特征、稀疏理論等不斷取得新的進展。為此,本文將這些新的理論和方法應用到視頻內容分析中,深入研究了視頻內容的特征提取與表征,然后將其應用到視頻近拷貝檢測以及視頻廣告內容的插入中。本文的研究內容主要包括以下幾個部分:1.提出了一種面向MPEG-2視頻的時空特征提取與表達方法針對現有視頻內容分析中提取的特征描述力不足的問題,結合視頻編碼格式的特點,提取MPEG-2視頻的時間和空間特征充分表征視頻內容。首先,利用視覺顯著性模型提取視頻關鍵幀,然后對關鍵幀提取HSV顏色直方圖、ORB特征(Oriented FAST and Rotated BRIEF)等空間特征,并對ORB特征進行稀疏表示,同時自MPEG-2碼流中直接提取運動矢量,對其繪制角度直方圖為視頻的時間特征。空間特征和時間特征相結合,得到多維度的視頻時空特征,來表征視頻內容。2.設計并實現了一種基于時空特征的MPEG-2視頻近拷貝檢測方法本文將提取的視頻時空特征表達應用于視頻近拷貝檢測技術中。通過分別比較各個特征的相似度,利用基于投票機制的決策融合方法,綜合得出查詢視頻與參考視頻內容相似度,從而給出近拷貝檢測結果。在標準數據集上的實驗結果顯示,本文提取的時空特征可以有效抵抗多種近拷貝變化,同時,提出的近拷貝檢測算法具有更優(yōu)的準確率和檢測速度。3.設計了一種基于內容的視頻廣告插入方法當前的視頻廣告插入方法是在固定的時間點上將廣告插入目標投放視頻,對視頻的播放過程造成嚴重干擾,極易引起瀏覽者對廣告商品的抵觸情緒。因此本文在現有的基于內容的廣告插入方法基礎上,對其進行了改進。本文算法根據視頻的時空特征與結構化特點,計算廣告與投放視頻之間的內容相似度,篩選出恰當的廣告插入位置,實現了基于內容的廣告插入。本文進行了主觀評價實驗,實驗結果表明,本文算法相較于定點插入方法,對瀏覽者的干擾較小。
[Abstract]:Video Content Analysis (VCA) has been one of the most concerned research topics in multimedia field. After many years of research, it has made some progress, and has been widely used in video near copy detection. Advertising and video retrieval and other areas. The key part of video content analysis is how to extract video features so as to describe video content effectively and comprehensively. In recent years, new advances have been made in image content analysis, image local features and sparse theory. Therefore, this paper applies these new theories and methods to video content analysis, studies the feature extraction and representation of video content, and then applies it to video near-copy detection and video advertising content insertion. The research content of this paper mainly includes the following several parts: 1. A spatio-temporal feature extraction and representation method for MPEG-2 video is proposed to solve the problem of insufficient description of features extracted from existing video content analysis, combined with the characteristics of video coding format. The temporal and spatial features of MPEG-2 video are extracted to fully represent the video content. Firstly, the video key-frame is extracted by visual saliency model, then the spatial features such as HSV color histogram Orb feature oriented FAST and Rotated BRIEF) are extracted from the key-frame, and the ORB features are represented sparsely, and the motion vector is extracted directly from the MPEG-2 bitstream. The angle histogram is the time feature of video. Combining spatial features with temporal features, a multi-dimensional video space-time feature is obtained to represent the video content. 2. This paper designs and implements a method of near copy detection for MPEG-2 video based on temporal and spatial features. In this paper, the extracted temporal and spatial feature representation of MPEG-2 video is applied to the near copy detection technology of video. By comparing the similarity of each feature and using the decision fusion method based on voting mechanism, the similarity of query video and reference video content is synthesized, and the result of near-copy detection is given. The experimental results on the standard data set show that the spatio-temporal features extracted in this paper can effectively resist a variety of near-copy changes. At the same time, the proposed near-copy detection algorithm has better accuracy and detection speed of .3. In this paper, a content-based video advertisement insertion method is designed. The current video advertisement insertion method is to insert the advertisement into the target video at a fixed point in time, which causes serious interference to the video playback process. It is easy to cause resistance to advertising products. Therefore, based on the existing content-based advertising insertion method, this paper improves it. According to the spatiotemporal and structural features of video, this algorithm calculates the content similarity between advertising and video delivery, selects the appropriate position of advertising insertion, and realizes content-based advertising insertion. The experimental results show that the proposed algorithm has less interference to the visitors than the fixed-point insertion method.
【學位授予單位】：北京工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TP391.41
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本文編號：1804620