DocumentCode :
2576676
Title :
Effective and efficient sports highlights extraction using the minimum description length criterion in selecting GMM structures [audio classification]
Author :
Xiong, Ziyou ; Radhakrishnan, Rathnakumar ; Divakaran, Ajay ; Huang, Thomas S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL, USA
Volume :
3
fYear :
2004
fDate :
27-30 June 2004
Firstpage :
1947
Abstract :
In fitting the training data with Gaussian mixture models (GMMs) of appropriate structures using the MDL (minimum description length) criterion, we are able to improve audio classification accuracy with a large margin. With the MDL-GMMs, we are also able to greatly improve the accuracy in extracting sports highlights. Since we have focused on audio domain processing, it enables us to extract highlights very quickly. We have demonstrated the importance of a better understanding of model structures in such a pattern recognition task.
Keywords :
Gaussian distribution; audio signal processing; classification; feature extraction; multimedia computing; GMM structures; Gaussian mixture models; MDL-GMM; audio classification accuracy; audio domain processing; minimum description length estimator; pattern recognition; sports highlights extraction; training data fitting; video analysis; Clustering algorithms; Data engineering; Data mining; Electronic mail; Feature extraction; Laboratories; Maximum likelihood estimation; Parameter estimation; Pattern recognition; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Expo, 2004. ICME '04. 2004 IEEE International Conference on
Print_ISBN :
0-7803-8603-5
Type :
conf
DOI :
10.1109/ICME.2004.1394642
Filename :
1394642
Link To Document :
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