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Online web video topic detection and tracking with semi-supervised learning

文献类型：期刊论文

作者Li, Guorong2; Jiang, Shuqiang3; Zhang, Weigang1; Pang, Junbiao4; Huang, Qingming2,3
刊名MULTIMEDIA SYSTEMS
出版日期2016-02-01
卷号22期号:1页码:115-125
关键词Topic detection and tracking Web video Multi-feature fusion Semi-supervised learning
ISSN号0942-4962
DOI10.1007/s00530-014-0402-0
英文摘要With the pervasiveness of online social media and rapid growth of web data, a large amount of multi-media data is available online. However, how to organize them for facilitating users' experience and government supervision remains a problem yet to be seriously investigated. Topic detection and tracking, which has been a hot research topic for decades, could cluster web videos into different topics according to their semantic content. However, how to online discover topic and track them from web videos and images has not been fully discussed. In this paper, we formulate topic detection and tracking as an online tracking, detection and learning problem. First, by learning from historical data including labeled data and plenty of unlabeled data using semi-supervised multi-class multi-feature method, we obtain a topic tracker which could also discover novel topics from the new stream data. Second, when new data arrives, an online updating method is developed to make topic tracker adaptable to the evolution of the stream data. We conduct experiments on public dataset to evaluate the performance of the proposed method and the results demonstrate its effectiveness for topic detection and tracking.
资助项目China Postdoctoral Science Foundation[2012M520436] ; National Basic Research Program of China (973 Program)[2012CB316400] ; National Natural Science Foundation of China[61303153] ; National Natural Science Foundation of China[61025011] ; National Natural Science Foundation of China[61332016] ; National Natural Science Foundation of China[61322212] ; National Natural Science Foundation of China[61202234] ; National Natural Science Foundation of China[61202322] ; Present Foundation of UCAS
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000368828500011
出版者SPRINGER
源URL[http://119.78.100.204/handle/2XEOYT63/8910]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Li, Guorong; Zhang, Weigang; Huang, Qingming
作者单位1.Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150006, Peoples R China
2.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing, Peoples R China
3.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China
4.Beijing Univ Technol, Beijing Municipal Key Lab Multimedia & Intelligen, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Li, Guorong,Jiang, Shuqiang,Zhang, Weigang,et al. Online web video topic detection and tracking with semi-supervised learning[J]. MULTIMEDIA SYSTEMS,2016,22(1):115-125.
APA Li, Guorong,Jiang, Shuqiang,Zhang, Weigang,Pang, Junbiao,&Huang, Qingming.(2016).Online web video topic detection and tracking with semi-supervised learning.MULTIMEDIA SYSTEMS,22(1),115-125.
MLA Li, Guorong,et al."Online web video topic detection and tracking with semi-supervised learning".MULTIMEDIA SYSTEMS 22.1(2016):115-125.

入库方式： OAI收割

来源：计算技术研究所

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