Segmentation and classification of meeting events using multiple classifier fusion and dynamic programming

Stephan Reiter, Gerhard Rigoll

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

22 Scopus citations

Abstract

In this paper the segmentation of a meeting into meeting events is investigated as well as the recognition of the detected segments. First the classification of a meeting event is examined. Five different classifiers are combined through multiple classifier fusion. Then a way for finding the optimal segment boundaries is presented. With a Dynamic Programming approach quite encouraging results can be obtained. The results show further that by classifier fusion a more stable result can be achieved than using only one single classifier.

Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
EditorsJ. Kittler, M. Petrou, M. Nixon
Pages434-437
Number of pages4
DOIs
StatePublished - 2004
EventProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom
Duration: 23 Aug 200426 Aug 2004

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume3
ISSN (Print)1051-4651

Conference

ConferenceProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
Country/TerritoryUnited Kingdom
CityCambridge
Period23/08/0426/08/04

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