Advanced news video parsing via visual characteristics of anchorperson scenes.
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| Title: | Advanced news video parsing via visual characteristics of anchorperson scenes. |
|---|---|
| Authors: | Dong, Yuan1 yuandong@bupt.edu.cn, Qin, Gang1 guorui.xiao@gmail.com, Xiao, Guorui1 qingang.bupt@gmail.com, Lian, Shiguo2 shiguo.lian@ieee.org, Chang, Xiaofu3 xiaofu.chang@orange-ftgroup.com |
| Source: | Telecommunication Systems. Nov2013, Vol. 54 Issue 3, p247-263. 17p. |
| Subjects: | Television programs, Linguistic String Parser (Computer grammar), Generative grammar, Television broadcasting, Mass media |
| Abstract: | In this paper, we present an advanced news video parsing system via exploring the visual characteristics of anchorperson scenes, which aims to provide personalized news services over Internet or mobile platforms. As the anchorperson shots serve as the root shots for constructing news video, the addressed system firstly performs anchorperson detection which divides the news into several segments. Due to the manipulation of multi-features and post-processing, our method of anchorperson detection can even be efficiently applied to news video whose anchorperson scenes are most challenging and complicated. Usually, the segments produced from anchorperson detection are regarded as news stories. However, an observation in our database proves this is not true because of the existing of interview scenes. These interview scenes are showed in the form that interviewer (anchorperson) and interviewee recursively appear. Thus, a technique called interview clustering based on face similarity is carried out to merge these interview segments. Another novel aspect of our system is entity summarization of interview scenes. We adopt it in the system at final. The effectiveness and robustness of the proposed system are demonstrated by the evaluation on 19 hours of news programs from 6 different TV Channels. [ABSTRACT FROM AUTHOR] |
| Copyright of Telecommunication Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Items | – Name: Title Label: Title Group: Ti Data: Advanced news video parsing via visual characteristics of anchorperson scenes. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Dong%2C+Yuan%22">Dong, Yuan</searchLink><relatesTo>1</relatesTo><i> yuandong@bupt.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Qin%2C+Gang%22">Qin, Gang</searchLink><relatesTo>1</relatesTo><i> guorui.xiao@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Xiao%2C+Guorui%22">Xiao, Guorui</searchLink><relatesTo>1</relatesTo><i> qingang.bupt@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Lian%2C+Shiguo%22">Lian, Shiguo</searchLink><relatesTo>2</relatesTo><i> shiguo.lian@ieee.org</i><br /><searchLink fieldCode="AR" term="%22Chang%2C+Xiaofu%22">Chang, Xiaofu</searchLink><relatesTo>3</relatesTo><i> xiaofu.chang@orange-ftgroup.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Telecommunication+Systems%22">Telecommunication Systems</searchLink>. Nov2013, Vol. 54 Issue 3, p247-263. 17p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Television+programs%22">Television programs</searchLink><br /><searchLink fieldCode="DE" term="%22Linguistic+String+Parser+%28Computer+grammar%29%22">Linguistic String Parser (Computer grammar)</searchLink><br /><searchLink fieldCode="DE" term="%22Generative+grammar%22">Generative grammar</searchLink><br /><searchLink fieldCode="DE" term="%22Television+broadcasting%22">Television broadcasting</searchLink><br /><searchLink fieldCode="DE" term="%22Mass+media%22">Mass media</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In this paper, we present an advanced news video parsing system via exploring the visual characteristics of anchorperson scenes, which aims to provide personalized news services over Internet or mobile platforms. As the anchorperson shots serve as the root shots for constructing news video, the addressed system firstly performs anchorperson detection which divides the news into several segments. Due to the manipulation of multi-features and post-processing, our method of anchorperson detection can even be efficiently applied to news video whose anchorperson scenes are most challenging and complicated. Usually, the segments produced from anchorperson detection are regarded as news stories. However, an observation in our database proves this is not true because of the existing of interview scenes. These interview scenes are showed in the form that interviewer (anchorperson) and interviewee recursively appear. Thus, a technique called interview clustering based on face similarity is carried out to merge these interview segments. Another novel aspect of our system is entity summarization of interview scenes. We adopt it in the system at final. The effectiveness and robustness of the proposed system are demonstrated by the evaluation on 19 hours of news programs from 6 different TV Channels. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Telecommunication Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11235-013-9731-0 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 247 Subjects: – SubjectFull: Television programs Type: general – SubjectFull: Linguistic String Parser (Computer grammar) Type: general – SubjectFull: Generative grammar Type: general – SubjectFull: Television broadcasting Type: general – SubjectFull: Mass media Type: general Titles: – TitleFull: Advanced news video parsing via visual characteristics of anchorperson scenes. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Dong, Yuan – PersonEntity: Name: NameFull: Qin, Gang – PersonEntity: Name: NameFull: Xiao, Guorui – PersonEntity: Name: NameFull: Lian, Shiguo – PersonEntity: Name: NameFull: Chang, Xiaofu IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2013 Type: published Y: 2013 Identifiers: – Type: issn-print Value: 10184864 Numbering: – Type: volume Value: 54 – Type: issue Value: 3 Titles: – TitleFull: Telecommunication Systems Type: main |
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