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Proceedings Paper

Video indexing based on image and sound
Author(s): Pascal Faudemay; Claude Montacie; Marie-Jose Caraty
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Paper Abstract

Video indexing is a major challenge for both scientific and economic reasons. Information extraction can sometimes be easier from sound channel than from image channel. We first present a multi-channel and multi-modal query interface, to query sound, image and script through 'pull' and 'push' queries. We then summarize the segmentation phase, which needs information from the image channel. Detection of critical segments is proposed. It should speed-up both automatic and manual indexing. We then present an overview of the information extraction phase. Information can be extracted from the sound channel, through speaker recognition, vocal dictation with unconstrained vocabularies, and script alignment with speech. We present experiment results for these various techniques. Speaker recognition methods were tested on the TIMIT and NTIMIT database. Vocal dictation as experimented on newspaper sentences spoken by several speakers. Script alignment was tested on part of a carton movie, 'Ivanhoe'. For good quality sound segments, error rates are low enough for use in indexing applications. Major issues are the processing of sound segments with noise or music, and performance improvement through the use of appropriate, low-cost architectures or networks of workstations.

Paper Details

Date Published: 6 October 1997
PDF: 13 pages
Proc. SPIE 3229, Multimedia Storage and Archiving Systems II, (6 October 1997); doi: 10.1117/12.290365
Show Author Affiliations
Pascal Faudemay, Univ. de Paris VI--Pierre et Marie Curie (France)
Claude Montacie, Univ. de Paris VI--Pierre et Marie Curie (France)
Marie-Jose Caraty, Univ. de Paris VI--Pierre et Marie Curie (France)


Published in SPIE Proceedings Vol. 3229:
Multimedia Storage and Archiving Systems II
C.-C. Jay Kuo; Shih-Fu Chang; Venkat N. Gudivada, Editor(s)

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