The use of kernel methods for audio events detection

The use of kernel methods for audio events detection

This paper presents an approach for an automatic surveillance system in public transport by analyzing audio signals recorded in the vehicle in order to detect several abnormal behaviors. We try to visualize audio signals by projection methods like PCA and kernel PCA. We use also unsupervised classif...

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Hauptverfasser: Nasser, A., Hamad, D., Rouas, J.-L., Ambellouis, S.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
audio detection
clustering
Clustering algorithms
Data mining
Data visualization
Event detection
Feature extraction
Kernel
Kernel methods
MFCC
Principal component analysis
projection
Signal analysis
Surveillance
Vehicles
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Beschreibung
Zusammenfassung:This paper presents an approach for an automatic surveillance system in public transport by analyzing audio signals recorded in the vehicle in order to detect several abnormal behaviors. We try to visualize audio signals by projection methods like PCA and kernel PCA. We use also unsupervised classification (clustering) methods to separate the audio signals into their components precisely we are using K- means and kernel K-means.
DOI:10.1109/ICTTA.2008.4529996