Open AccessMultimodal Approach for Summarizing and Indexing News Video
Author(s) -
Kim JaeGon,
Chang Hyun Sung,
Kim Youngtae,
Kang Kyeongok,
Kim Munchurl,
Kim Jinwoong,
Kim HyungMyung
Publication year - 2002
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.02.0102.0101
Subject(s) - computer science , automatic summarization , search engine indexing , information retrieval , smacker video , citation , video tracking , world wide web , multimedia , video processing , artificial intelligence
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.