Title :
The use of kernel methods for audio events detection
Author :
Nasser, Alissar ; Hamad, Denis ; Rouas, Jean-Luc ; Ambellouis, Sébastien
Author_Institution :
LASL/ULCO, Calais
Abstract :
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.
Keywords :
audio signal processing; pattern clustering; signal classification; signal detection; source separation; surveillance; abnormal behavior detection; audio event detection; audio signal separation; audio signal visualization; audio signals analysis; automatic surveillance system; kernel k-means method; public transport; unsupervised classification method; unsupervised clustering method; Clustering algorithms; Data mining; Data visualization; Event detection; Feature extraction; Kernel; Principal component analysis; Signal analysis; Surveillance; Vehicles; Kernel methods; MFCC; audio detection; clustering; projection;
Conference_Titel :
Information and Communication Technologies: From Theory to Applications, 2008. ICTTA 2008. 3rd International Conference on
Conference_Location :
Damascus
Print_ISBN :
978-1-4244-1751-3
Electronic_ISBN :
978-1-4244-1752-0
DOI :
10.1109/ICTTA.2008.4529996
