Structuring Sport Video through Audio Event Classification
Automatic audio information retrieval is facing great challenge due to the advances of information technology, more and more digital audio, images and video are being captured, produced and stored. To develop an automatic audio signal classification for a large dataset, building audio classifier is still challenging in existing work. In this proposed system we combine the two classifiers, SVM and decision tree, to classify the video information. To classify the audio information by using decision tree, the SVM is applied as a decision for feature selection. The aim is to achieve high accuracy in classifying of mixed types audio by combining two types of classifiers. In this proposed system four audio classes are considered and this classification and analysis is intended to analyze the structure of the sports video. Soccer videos are experimented in this system and experimental study indicates that the proposed framework can produce satisfactory results.
KeywordsSupport Vector Machine Support Vector Machine Classifier Audio Signal Audio Feature Sport Video
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