By Topic

A novel violent videos classification scheme based on the bag of audio words features [Document Suppressed in IEEE Xplore]

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Lei Li ; Comput. Sci. Dept., Carnegie Mellon Univ., Pittsburgh, PA, USA

[This paper has been withdrawn by the publisher]. A novel method to identify the violent videos only with audio features is introduced. Most previous content-based image or video classification schemes apply the bag of words (BOW) or bag of visual words (BOVW), which employ multiple visual features to characterize image or video content. In our method, the bag of audio words (BOAW) is suggested to be built by effective audio features. Two reasons are considered here. First, audio features should have very special significance for violent videos. Second, the computational complexity of dealing with audio features is much lower than that of visual features. The MPEG-7 low level features such as Audio Spectrum-Centroid and Audio Spectrum-Spread, and the high level feature such as Audio Signature, are combined into one 44-dimensions vector in the BOAW model. The audio words are built from the vector by the clustering strategy, and support vector machine (SVM) with revised soft-weighting scheme is used to group the audio words features into two classes, i.e. the violent and non-violent. Experiments demonstrate that the proposed method can achieve good recall accuracy and precision accuracy on detecting violent videos. The method also can be applied to classify other types of videos.

Note: Document Suppressed in IEEE Xplore. The document that should appear here has been removed because it was submitted for publication without proper authorization. The article was not written by the author of record noted in the bibliographic data. Mr. Li was neither aware of this having been published in his name, nor is he responsible for any content as written. We regret any inconvenience.  

Published in:

Information Technology: New Generations (ITNG), 2012 Ninth International Conference on

Date of Conference:

16-18 April 2012