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UDC 004.275, DOI: 10.2298/CSIS1001085S

Multi-Video Summarization Using Complex Graph Clustering and Mining

Jian Shao¹, Dongming Jiang¹, Mengru Wang², Hong Chen² and Lu Yao¹

1. College of Computer Science, Zhejiang University
   310027 Hangzhou, P. R. China
   jshao@cs.zju.edu.cn, dmjiang1985@163.com, cs08yl@hotmail.com
2. Zhejiang Radio & TV Group
   310005 Hangzhou, P. R. China
   {wmr628, ch213}@mail.zrtg.com

Abstract

Multi-video summarization is a great theoretical and technical challenge due to the wider diversity of topics in multi-video than single-video as well as the multi-modality nature of multi-video over multi-document. In this paper, we propose an approach to analyze both visual and textual features across a set of videos and to create a so-called circular storyboard composed of topic-representative keyframes and keywords. We formulate the generation of circular storyboard as a problem of complex graph clustering and mining, in which each separated shot from visual data and each extracted keyword from speech transcripts are first structured into a complex graph and grouped into clusters; hidden topics in the representative keyframes and keywords are then mined from clustered complex graph while at the same time maximizing the coverage of the summary over the original video set. We also design experiments to evaluate the effectiveness of our approach and the proposed approach shows a better performance than two other storyboard baselines.

Key words

multi-video summarization, complex graph clustering and mining, circular storyboard

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS1001085S

Publication information

Volume 7, Issue 1 (February 2010)
Advances in Computer Animation and Digital Entertainment
Year of Publication: 2010
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Shao, J., Jiang, D., Wang, M., Chen, H., Yao, L.: Multi-Video Summarization Using Complex Graph Clustering and Mining. Computer Science and Information Systems, Vol. 7, No. 1. (2010), https://doi.org/10.2298/CSIS1001085S