基于MPEG-2的视频内容分析技术与应用研究

发布时间：2018-04-26 05:11

  本文选题：视频内容分析 + MPEG-2　； 参考：《北京工业大学》2016年硕士论文

【摘要】：视频内容分析(Video Content Analysis,VCA)一直是多媒体领域最受关注的研究课题之一,经过多年的研究,取得了一定的研究进展,目前已广泛应用于视频近拷贝检测、广告投放以及视频检索等多个领域。视频内容分析的关键部分在于如何提取视频特征,从而对视频内容进行有效、全面的描述。近年来,图像内容分析技术、图像局部特征、稀疏理论等不断取得新的进展。为此,本文将这些新的理论和方法应用到视频内容分析中,深入研究了视频内容的特征提取与表征,然后将其应用到视频近拷贝检测以及视频广告内容的插入中。本文的研究内容主要包括以下几个部分:1.提出了一种面向MPEG-2视频的时空特征提取与表达方法针对现有视频内容分析中提取的特征描述力不足的问题,结合视频编码格式的特点,提取MPEG-2视频的时间和空间特征充分表征视频内容。首先,利用视觉显著性模型提取视频关键帧,然后对关键帧提取HSV颜色直方图、ORB特征(Oriented FAST and Rotated BRIEF)等空间特征,并对ORB特征进行稀疏表示,同时自MPEG-2码流中直接提取运动矢量,对其绘制角度直方图为视频的时间特征。空间特征和时间特征相结合,得到多维度的视频时空特征,来表征视频内容。2.设计并实现了一种基于时空特征的MPEG-2视频近拷贝检测方法本文将提取的视频时空特征表达应用于视频近拷贝检测技术中。通过分别比较各个特征的相似度,利用基于投票机制的决策融合方法,综合得出查询视频与参考视频内容相似度,从而给出近拷贝检测结果。在标准数据集上的实验结果显示,本文提取的时空特征可以有效抵抗多种近拷贝变化,同时,提出的近拷贝检测算法具有更优的准确率和检测速度。3.设计了一种基于内容的视频广告插入方法当前的视频广告插入方法是在固定的时间点上将广告插入目标投放视频,对视频的播放过程造成严重干扰,极易引起浏览者对广告商品的抵触情绪。因此本文在现有的基于内容的广告插入方法基础上,对其进行了改进。本文算法根据视频的时空特征与结构化特点,计算广告与投放视频之间的内容相似度,筛选出恰当的广告插入位置,实现了基于内容的广告插入。本文进行了主观评价实验,实验结果表明,本文算法相较于定点插入方法,对浏览者的干扰较小。
[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.
【学位授予单位】：北京工业大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP391.41
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本文编号：1804620