DocumentCode :
2569548
Title :
Automatic detection of Flash movie genre using Bayesian approach
Author :
Ding, Dawei ; Yang, Jun ; Li, Qing ; Wang, Liping ; Wenyin, Liu
Author_Institution :
Dept. of Comput. Eng. & Inf. Technol., City Univ. of Hong Kong
Volume :
1
fYear :
2004
fDate :
30-30 June 2004
Firstpage :
603
Abstract :
As Flash, a relatively new rich media format, becomes more and more popular on the Web, the genre becomes increasingly important for Flash movie management as a complement to topical principles of classification. Genre classification can identify Flash movies authored in a style most likely to satisfy a user´s information need. We present a method for detecting the Flash genre quickly and easily by employing a Bayesian approach. A feature set for representing genre information is proposed and used to build automatic genre classification algorithms. The performance of the proposed approach is evaluated by training a Bayesian classifier on real-world data sets. Classification results from our experiments on thousands of Flash movies demonstrate the usefulness of this approach
Keywords :
Bayes methods; image classification; multimedia computing; Bayesian classifier; Web; automatic Flash movie detection; feature set; genre classification; movie management; rich media format; Bayesian methods; Computer science; Content based retrieval; Fires; Information technology; Internet; Motion pictures; Statistics; Technology management; Web pages;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Expo, 2004. ICME '04. 2004 IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
0-7803-8603-5
Type :
conf
DOI :
10.1109/ICME.2004.1394264
Filename :
1394264
Link To Document :
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