Incorporating domain knowledge with video and voice data analysis in news broadcasts

Shearer, Kim, Dorai, Chitra and Venkatesh, Svetha 2000, Incorporating domain knowledge with video and voice data analysis in news broadcasts, in MDM/KDD 2000 : Proceedings of the 1st Workshop on Multimedia Data Mining, [Association for Computing Machinery], [New York, N. Y.], pp. 46-53.

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Title Incorporating domain knowledge with video and voice data analysis in news broadcasts
Author(s) Shearer, Kim
Dorai, Chitra
Venkatesh, Svetha
Conference name Workshop on Multimedia Data Mining (1st : 2000 : Boston, Mass.)
Conference location Boston, Mass.
Conference dates 20 Aug. 2000
Title of proceedings MDM/KDD 2000 : Proceedings of the 1st Workshop on Multimedia Data Mining
Editor(s) Simoff, Simeon J.
Zaïane, Osmar R.
Publication date 2000
Conference series Workshop on Multimedia Data Mining
Start page 46
End page 53
Total pages 8
Publisher [Association for Computing Machinery]
Place of publication [New York, N. Y.]
Keyword(s) video annotation
domain knowledge
algorithm fusion
Summary This paper addresses the area of video annotation, indexing and retrieval, and shows how a set of tools can be employed, along with domain knowledge, to detect narrative structure in broadcast news. The initial structure is detected using low-level audio visual processing in conjunction with domain knowledge. Higher level processing may then utilize the initial structure detected to direct processing to improve and extend the initial classification.

The structure detected breaks a news broadcast into segments, each of which contains a single topic of discussion. Further the segments are labeled as a) anchor person or reporter, b) footage with a voice over or c) sound bite. This labeling may be used to provide a summary, for example by presenting a thumbnail for each reporter present in a section of the video. The inclusion of domain knowledge in computation allows more directed application of high level processing, giving much greater efficiency of effort expended. This allows valid deductions to be made about structure and semantics of the contents of a news video stream, as demonstrated by our experiments on CNN news broadcasts.
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2000, The Authors
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044760

Document type: Conference Paper
Collection: School of Information Technology
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