On application-unbiased benchmarking of web videos from a social network perspective

doi:10.1007/s11042-014-2245-2

	On application-unbiased benchmarking of web videos from a social network perspective
	Cao, Juan 1; Zhang, Yongdong 1; Ji, Rongrong 1; Li, Xin 2
	2016-02-01
发表期刊	MULTIMEDIA TOOLS AND APPLICATIONS
ISSN	1380-7501
卷号	75 期号:3 页码:1543-1556
摘要	Along with the emerging focus of community-contributed videos on the web, there is a strong demand of a well-designed web video benchmark for the research of social network based video content analysis. The existing video datasets are challenged in two aspects: (1) as the data resource, most of them are narrowed for a specific task, either focusing on one content analysis task with limited scales, or focusing on the pure social network analysis without downloading video content. (2) as the evaluation platform, few of them pay attention to the potential bias introduced by the sampling criteria, therefore cannot fairly measure the task performance. In this paper, we release a large-scale web video benchmark named MCG-WEBV 2.0, which crawls 248,887 YouTube videos and their corresponding social network structure with 123,063 video contributors. MCG-WEBV 2.0 can be used to explore the fusion between content and network for several web video analysis tasks. Based on MCG-WEBV 2.0, we further explore the sampling bias lies in web video benchmark construction. While sampling a completely unbiased video benchmark from million-scale collection is unpractical, we propose a task-dependent measurement of such bias, which minimizes the correlation between the potential video sampling bias and the corresponding content analysis task, if such bias is unavoidable. Following this principle, we have shown several exemplar application scenarios in MCG-WEBV 2.0.
关键词	Web video benchmark Social network Sampling bias MCG-WEBV 2.0
DOI	10.1007/s11042-014-2245-2
收录类别	SCI
语种	英语
资助项目	National High Technology Research and Development Program of China[2014AA015202] ; National Nature Science Foundation of China[61172153] ; National Nature Science Foundation of China[61100087] ; National Key Technology Research and Development Program of China[2012BAH39B02] ; Beijing New Star Project on Science Technology[2007B071]
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000371309600012
出版者	SPRINGER
引用统计	被引频次：2[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/8614
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhang, Yongdong
作者单位	1.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing, Peoples R China 2.Tsinghua Univ, Dept Comp Sci & Technol, Beijing 100084, Peoples R China
推荐引用方式 GB/T 7714	Cao, Juan,Zhang, Yongdong,Ji, Rongrong,et al. On application-unbiased benchmarking of web videos from a social network perspective[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2016,75(3):1543-1556.
APA	Cao, Juan,Zhang, Yongdong,Ji, Rongrong,&Li, Xin.(2016).On application-unbiased benchmarking of web videos from a social network perspective.MULTIMEDIA TOOLS AND APPLICATIONS,75(3),1543-1556.
MLA	Cao, Juan,et al."On application-unbiased benchmarking of web videos from a social network perspective".MULTIMEDIA TOOLS AND APPLICATIONS 75.3(2016):1543-1556.