Audio-Video based Segmentation and Classification Using SVM

被引：0
作者：
Subashini, K. [1 ]
Palanivel, S.
Ramaligam, V. [2 ]
机构：
[1] Annamalai Univ, Chidambaram 608002, India
[2] Annamalai Univ, Dept Comp Sci & Engn, Chidambaram, India
来源：
2012 THIRD INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION & NETWORKING TECHNOLOGIES (ICCCNT) | 2012年
关键词：
Support vector machines; Mel frequency cepstral coefficients; Color histogram; Audio classification; Video classification; Audio-video classification;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we propose a method for combining audio and video for segmentation and classification. The objective of segmentation is to detect category change point such as news followed by advertisement. The classification system classify the audio and video data into one of the predefined categories such as news, advertisement, sports, serial and movies. Automatic audio-video classification is very useful to audio-video indexing, content based audio-video retrieval. Mel frequency cepstral coefficients is used as acoustic features and color histogram is used as visual features for segmentation and classification. Support vector machine (SVM) is used for both segmentation and classification. The experiments on different genres illustrate the results of classification are significant. Experimental results of audio classification evidence and video are combined using weighted sum rule for audio-video based segmentation and classification.
引用
收藏
页数：6
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