TF-RNF: A novel term weighting scheme for sports video classification
Date
2012
ISBN
978-146732193-8
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Volume Title
Resource Type
Conference paper
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Journal Title
TF-RNF: A novel term weighting scheme for sports video classification
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Abstract
Determination of content importance is very important in achieving high quality classification. Term weighting schemes in text classification will be applied to classify videos by measuring importance of video contents. In other words, a video sequence can be treated as a document, and frames of a video are considered as words or terms which identify contents of a video. And to enhance the efficiency of video classification, this paper proposes a novel term weighting scheme, called the Term Frequency - Relevance and Non-relevance Frequency (TF-RNF) weighting. This technique can filter both relevant and non-relevant contents so as to reduce classification errors. Empirical evaluations of results show that the proposed technique significantly outperforms traditional techniques in sports video classification. © 2012 IEEE.
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Citation
2012 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2012