A Study on Shot Segmentation and Indexing of Language Education Videos by Content-based Visual Feature Analysis

Heejun Han (한희준)

doi:10.3743/KOSIM.2017.34.1.219

A Study on Shot Segmentation and Indexing of Language Education Videos by Content-based Visual Feature Analysis

Journal of the Korean Society for Information Management
Abbr : JKOSIM
2017, 34(1), pp.219~239
DOI : 10.3743/KOSIM.2017.34.1.219
Publisher : 한국정보관리학회
Research Area : Interdisciplinary Studies > Library and Information Science
Received : February 21, 2017
Accepted : March 13, 2017
Published : March 30, 2017

Heejun Han ¹

¹경기대학교 대학원 문헌정보학과

Accredited

ABSTRACT

As IT technology develops rapidly and the personal dissemination of smart devices increases, video material is especially used as a medium of information transmission among audiovisual materials. Video as an information service content has become an indispensable element, and it has been used in various ways such as unidirectional delivery through TV, interactive service through the Internet, and audiovisual library borrowing. Especially, in the Internet environment, the information provider tries to reduce the effort and cost for the processing of the provided information in view of the video service through the smart device. In addition, users want to utilize only the desired parts because of the burden on excessive network usage, time and space constraints. Therefore, it is necessary to enhance the usability of the video by automatically classifying, summarizing, and indexing similar parts of the contents. In this paper, we propose a method of automatically segmenting the shots that make up videos by analyzing the contents and characteristics of language education videos and indexing the detailed contents information of the linguistic videos by combining visual features. The accuracy of the semantic based shot segmentation is high, and it can be effectively applied to the summary service of language education videos.

KEYWORDS

shot segmentation, keyframe extraction, content-based summary, language education video, shot indexing

Citation status

* References for papers published after 2023 are currently being built.

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Journal of the Korean Society for Information Management 2023 KCI Impact Factor : 1.31

A Study on Shot Segmentation and Indexing of Language Education Videos by Content-based Visual Feature Analysis

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* References for papers published after 2023 are currently being built.

Journal of the Korean Society for Information Management 2023 KCI Impact Factor : 1.31

A Study on Shot Segmentation and Indexing of Language Education Videos by Content-based Visual Feature Analysis

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KEYWORDS

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