Research on bag of audio words algorithm in the violent videos classification

Author

Xinghao Jiang ; Tanfeng Sun ; Rongjie Li ; Bing Feng ; GuangLei Fu ; Shilin Wang ; Xinghao Jiang ; Tanfeng Sun

Volume

1

fYear

2010

fDate

16-18 Oct. 2010

Firstpage

395

Lastpage

399

Abstract

In this paper, a new method to identify the violent videos by the bag of audio words is introduced. The MPEG-7 audio descriptors are firstly extracted, including the low level features such as AudioSpectrumCentroid and AudioSpectrum-Spread, etc. The audio words are then built according to the MPEG-7 high level descriptor, the AudioSighnature, which is considered as the “fingerprint” of the audio stream. The support vector machine is used to classify the feature vectors into two classes, i.e. the violent and non-violent videos. The experiment results demonstrate that our method can achieve good recall accuracy.

Keywords

audio signal processing; audio streaming; feature extraction; support vector machines; AudioSighnature; AudioSpectrum-Spread; AudioSpectrumCentroid; MPEG-7 audio descriptors; MPEG-7 high level descriptor; audio stream; audio words algorithm; fingerprint; support vector machine; violent videos classification; Accuracy; Feature extraction; Support vector machines; Training; Transform coding; Videos; Visualization; MPEG-7 audio descriptors; bag of words; support vector machine; violent video; weighting scheme;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing (CISP), 2010 3rd International Congress on

Conference_Location

Yantai

Print_ISBN

978-1-4244-6513-2

Type

conf

DOI

10.1109/CISP.2010.5648004

Filename

5648004