Efficient Video Shot Summarization Using an Enhanced Spectral Clustering Approach

Authors:
Vasileios Chasanis;Aristidis Likas;Nikolaos Galatsanos
Affiliations:
Department of Computer Science, University of Ioannina, Ioannina, Greece 45110;Department of Computer Science, University of Ioannina, Ioannina, Greece 45110;Department of Computer Science, University of Ioannina, Ioannina, Greece 45110
Venue:
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Year:
2008

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Abstract

Video summarization is a powerful tool to handle the huge amount of data generated every day. At shot level, the key-frame extraction problem provides sufficient indexing and browsing of large video databases. In this paper we propose an approach that estimates the number of key-frames using elements of the spectral graph theory. Next, the frames of the video sequence are clustered into groups using an improved version of the spectral clustering algorithm. Experimental results show that our algorithm efficiently summarizes the content of a video shot producing unique and representative key-frames outperforming other methods.