Title :
Using multiclass SVM and MP for audio recognition of action scenes
Author :
Xiaohui, Wang ; FengJuan, Guo
Author_Institution :
Sch. of Comput. Sci. & Technol., North China Electr. Power Univ., Baoding, China
Abstract :
The paper presents a system for sounds classification of action scenes. We propose to use the matching pursuit (MP) algorithm to obtain effective time-frequency features. The MP-based method utilizes a dictionary of atoms for feature selection, resulting in a flexible, intuitive and physically interpretable set of features. Then apply multiclass support vector machine based on improved binary tree algorithm to classify the sounds. The paper considers six type sounds: the sword sound, the club sound, the unarmed sound, the broken sound, the metal-falling sound and the shout sound. Experimental results prove that the method is effective.
Keywords :
audio signal processing; pattern classification; support vector machines; trees (mathematics); action scenes; audio recognition; binary tree; feature selection; matching pursuit; multiclass SVM; multiclass support vector machine; sounds classification; time-frequency features; Classification algorithms; Gabor atom; audio feature; binary tree; matching pursuit; multiclass SVM;
Conference_Titel :
Advances in Energy Engineering (ICAEE), 2010 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-7831-6
DOI :
10.1109/ICAEE.2010.5557564