广告实时标识系统研究与实现
发布时间：2019-06-14 14:28
【摘要】：直播电视产品已经广泛的走入了人们的日常生活中,如CNTV现已拥有央视直播、卫视直播、城市直播、数字直播,共140余路高清直播,并且数目还在不断增加,全国各省级、市级、地级的数字直播频道,已经逐步被完全覆盖。直播电视主要由不同种类的电视节目构成,如新闻资讯类、电视谈话类、文艺类、娱乐类、记录片类等等。能够运用计算机设备,实时高效的判定各种电视节目的具体类别,这种技术将是非常具有科研意义和实际应用价值的。广告实时检测系统选取的切入点是直播电视节目,通过对广告片段判定算法进行深入细致的研究,用基于学习的视频类别判定技术和切合实际的应用程序架构,来实时的分析和标注直播电视节目中的广告片段,并实现了从视频采集到结果展示的完整系统,省去了人工标注视频资料的耗费,使视频分类算法转化成了生产力。基于内容的视频类别判定技术是多媒体研究领域中的一个重要课题。首先,基于内容的视频判定技术可以运用于日益增加的视频数据管理、分类储存和视频内容检索上；其次,基于内容的视频类别判定技术可以有效的管理网络视频媒体的海量视频,自动维护更新数据库的标签,支持用户对视频的检索与查找；最后,基于内容的视频类别判定技术可以用在不良视频审查以及国家控制内容审查上,对巨量的视频数据中的违规违禁内容进行筛选、剔除或报警。本系统实现了基于内容的广告视频类别实时标注与判定算法,能达到在线运行演示效果的效率。本文研究了使用视频内容特征做视频分类的技术,针对直播电视中广告视频的判定,采用真实的CNTV数据作实验,取得到了良好的效果,实现了完整的实时的在线识别广告的系统。利用广告镜头的尾帧(EFC)特性,提取具有代表性的图像特征,采用SVM分类的方法区分广告尾帧；结合广告时长的统计特征作为后处理阈值判断,划分广告片段；并且对算法做了很多工程上的优化,能实时的展现识别效果。本文的主要特点是：该系统有着很高的广告边界定位精度,识别的广告尾部和实际的广告尾部极为接近；广告片段识别准确率较高,可达到83%以上；并且算法效率很高,使得系统可以实时地运行在CNTV在线视频上。
[Abstract]:Live TV products have been widely into people's daily life, such as CNTV now has CCTV live broadcast, satellite TV live broadcast, urban live broadcast, digital live broadcast, a total of more than 140th high-definition live broadcast, and the number is still increasing, the provincial, municipal and prefectural digital live broadcast channels have been gradually fully covered. Live TV is mainly composed of different kinds of TV programs, such as news and information, TV conversation, literature and art, entertainment, documentary and so on. It is of great scientific research significance and practical application value to be able to use computer equipment to determine the specific categories of various TV programs in real time and efficiently. The starting point of advertising real-time detection system is live TV program. Through the thorough and detailed research on the algorithm of advertising segment determination, the video category determination technology based on learning and the practical application program architecture are used to analyze and mark the advertisement fragment in live TV program in real time, and the complete system from video capture to result display is realized, which saves the cost of manually marking video data. The video classification algorithm is transformed into productivity. Content-based video category determination technology is an important topic in the field of multimedia research. Firstly, content-based video decision technology can be used in increasing video data management, classification storage and video content retrieval. Secondly, content-based video category decision technology can effectively manage the massive video of network video media, automatically maintain and update the label of the database, and support users to search and find video. Finally, content-based video category determination technology can be used in bad video review and state-controlled content review to screen, eliminate or alarm a large number of illegal and illegal content in video data. This system realizes the real-time tagging and judging algorithm of advertising video category based on content, and can achieve the efficiency of running demonstration effect online. In this paper, the technology of video classification using video content features is studied. aiming at the determination of advertising video in live TV, the real CNTV data is used as an experiment, and good results are obtained, and a complete real-time online identification advertising system is realized. Using the (EFC) characteristics of the tail frame of the advertising lens, the representative image features are extracted, and the SVM classification method is used to distinguish the tail frame of the advertisement. Combined with the statistical features of the advertising time length as the post-processing threshold to judge, the advertising fragments are divided. And a lot of engineering optimization of the algorithm is made, which can show the recognition effect in real time. The main characteristics of this paper are as follows: the system has high accuracy of advertising boundary location, the recognition of advertising tail is very close to the actual advertising tail; the accuracy of advertising segment recognition is high, up to 83%; and the algorithm efficiency is very high, so that the system can run on CNTV online video in real time.
【学位授予单位】：复旦大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP18;TN949.1
本文编号：2499457
[Abstract]:Live TV products have been widely into people's daily life, such as CNTV now has CCTV live broadcast, satellite TV live broadcast, urban live broadcast, digital live broadcast, a total of more than 140th high-definition live broadcast, and the number is still increasing, the provincial, municipal and prefectural digital live broadcast channels have been gradually fully covered. Live TV is mainly composed of different kinds of TV programs, such as news and information, TV conversation, literature and art, entertainment, documentary and so on. It is of great scientific research significance and practical application value to be able to use computer equipment to determine the specific categories of various TV programs in real time and efficiently. The starting point of advertising real-time detection system is live TV program. Through the thorough and detailed research on the algorithm of advertising segment determination, the video category determination technology based on learning and the practical application program architecture are used to analyze and mark the advertisement fragment in live TV program in real time, and the complete system from video capture to result display is realized, which saves the cost of manually marking video data. The video classification algorithm is transformed into productivity. Content-based video category determination technology is an important topic in the field of multimedia research. Firstly, content-based video decision technology can be used in increasing video data management, classification storage and video content retrieval. Secondly, content-based video category decision technology can effectively manage the massive video of network video media, automatically maintain and update the label of the database, and support users to search and find video. Finally, content-based video category determination technology can be used in bad video review and state-controlled content review to screen, eliminate or alarm a large number of illegal and illegal content in video data. This system realizes the real-time tagging and judging algorithm of advertising video category based on content, and can achieve the efficiency of running demonstration effect online. In this paper, the technology of video classification using video content features is studied. aiming at the determination of advertising video in live TV, the real CNTV data is used as an experiment, and good results are obtained, and a complete real-time online identification advertising system is realized. Using the (EFC) characteristics of the tail frame of the advertising lens, the representative image features are extracted, and the SVM classification method is used to distinguish the tail frame of the advertisement. Combined with the statistical features of the advertising time length as the post-processing threshold to judge, the advertising fragments are divided. And a lot of engineering optimization of the algorithm is made, which can show the recognition effect in real time. The main characteristics of this paper are as follows: the system has high accuracy of advertising boundary location, the recognition of advertising tail is very close to the actual advertising tail; the accuracy of advertising segment recognition is high, up to 83%; and the algorithm efficiency is very high, so that the system can run on CNTV online video in real time.
【学位授予单位】：复旦大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP18;TN949.1
【共引文献】
相关硕士学位论文 前1条
1 刘淑荣;基于语义的视频检索关键技术研究[D];华北电力大学;2013年
，本文编号：2499457
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