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

doi:10.1007/s00530-014-0402-0

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	Online web video topic detection and tracking with semi-supervised learning
	Li, Guorong 2; Jiang, Shuqiang 3; Zhang, Weigang 1; Pang, Junbiao 4; Huang, Qingming 2,3
刊名	MULTIMEDIA SYSTEMS
	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
DOI	10.1007/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
出版者	SPRINGER
WOS记录号	WOS:000368828500011
内容类型	期刊论文
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.