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Published in:
2010 | OriginalPaper | Chapter
Dangerous Sound Event Recognition Using Support Vector Machine Classifiers
Authors : Kuba Łopatka, Paweł Zwan, Andrzej Czyżewski
Published in: Advances in Multimedia and Network Information System Technologies
Publisher: Springer Berlin Heidelberg
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A method of recognizing events connected to danger based on their acoustic representation through Support Vector Machine classification is presented. The method proposed is particularly useful in an automatic surveillance system. The set of 28 parameters used in the classifier consists of dedicated parameters and MPEG-7 features. Methods for parameter calculation are presented, as well as a design of SVM model used for classification. The performance of the classifier was tested on a set of 372 example sounds, yielding high accuracy.