Multimodal Approach for Summarizing and Indexing News Video

  • Kim, Jae-Gon (Broadcasting Media Technology Department, Electronics and Telecommunications Research Institute (ETRI)) ;
  • Chang, Hyun-Sung (Broadcasting Media Technology Department, Electronics and Telecommunications Research Institute (ETRI)) ;
  • Kim, Young-Tae (Broadcasting Media Technology Department, Electronics and Telecommunications Research Institute (ETRI)) ;
  • Kang, Kyeong-Ok (Broadcasting Media Technology Department, Electronics and Telecommunications Research Institute (ETRI)) ;
  • Kim, Mun-Churl (School of Engineering, Information and Communications University (ICU)) ;
  • Kim, Jin-Woong (Broadcasting Media Technology Department, Electronics and Telecommunications Research Institute (ETRI)) ;
  • Kim, Hyung-Myung (Department of Electrical Engineering and Computer Science, Korea Advanced Institute of Science and Technology (KAIST))
  • Received : 2001.06.27
  • Published : 2002.02.28

Abstract

A video summary abstracts the gist from an entire video and also enables efficient access to the desired content. In this paper, we propose a novel method for summarizing news video based on multimodal analysis of the content. The proposed method exploits the closed caption data to locate semantically meaningful highlights in a news video and speech signals in an audio stream to align the closed caption data with the video in a time-line. Then, the detected highlights are described using MPEG-7 Summarization Description Scheme, which allows efficient browsing of the content through such functionalities as multi-level abstracts and navigation guidance. Multimodal search and retrieval are also within the proposed framework. By indexing synchronized closed caption data, the video clips are searchable by inputting a text query. Intensive experiments with prototypical systems are presented to demonstrate the validity and reliability of the proposed method in real applications.

Keywords

References

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