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Folk dance recognition using a bag of words approach and ISA/STIP features

Published:19 September 2013Publication History

ABSTRACT

Recognition of folk dances i.e. classification of dance videos according to the specific dance depicted can be considered a challenging sub task within the general activity recognition area because of the large number of different dances, the similarities among them and the different styles a dance can be performed. A method able to identify various folk dances is very important for analyzing and annotating multimedia databases of such dances thus helping the preservation of folk dance culture. In this paper, we deal with recognition of Greek folk dances. Clustering is applied on input features to extract a codedbook and a bag of words approach is applied. An SVM classifier is used for the classification. Two state of the art methods for feature extraction are used and compared. The method is applied on two folk dances from the Western Macedonia region.

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  1. Folk dance recognition using a bag of words approach and ISA/STIP features

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              cover image ACM Other conferences
              BCI '13: Proceedings of the 6th Balkan Conference in Informatics
              September 2013
              293 pages
              ISBN:9781450318518
              DOI:10.1145/2490257

              Copyright © 2013 ACM

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              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 19 September 2013

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              BCI '13 Paper Acceptance Rate41of103submissions,40%Overall Acceptance Rate97of250submissions,39%

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