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

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.

I. Introduction

With the flourishing of the moving industry and development of the multimedia, many types of movies are available through the internet. We can easily differentiate among different genres of movies after watching them. However, for the computer, it is a quite complicate work to automatically recognize the theme of various types of the movies. Furthermore, there are some films with many violent and horror scenes which are uncomfortable for children to watch.