A novel CBCD scheme based on local features category

Authors:
Jie Hou;Baolong Guo;Jinfu Wu
Affiliations:
Institute of Intelligent Control and Image Engineering (ICIE), Xidian University, Xian, China;Institute of Intelligent Control and Image Engineering (ICIE), Xidian University, Xian, China;Institute of Intelligent Control and Image Engineering (ICIE), Xidian University, Xian, China
Venue:
WISM'12 Proceedings of the 2012 international conference on Web Information Systems and Mining
Year:
2012

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Abstract

Global and local features have been applied extensively to improve the performance of Content-Based Copy Detection (CBCD) systems. A novel CBCD scheme which uses global features to category local features is proposed in this paper, containing frame prerecession, database establishment and copy detection. The scheme aims to reach a fast speed and a high accuracy. A proper combination of global and local features in our scheme breeds higher efficiency and accuracy than taking use of any single feature alone. Experimental results indicate that the scheme achieves a rapid scene index and an accuracy frame-frame match.