Rushes summarization with self-organizing maps

Authors:
Markus Koskela;Mats Sjöberg;Jorma Laaksonen;Ville Viitaniemi;Hannes Muurinen
Affiliations:
Helsinki University of Technology, Espoo, Finland;Helsinki University of Technology, Espoo, Finland;Helsinki University of Technology, Espoo, Finland;Helsinki University of Technology, Espoo, Finland;Helsinki University of Technology, Espoo, Finland
Venue:
Proceedings of the international workshop on TRECVID video summarization
Year:
2007

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Abstract

In this paper, we describe our approach for video summarization that was applied to the BBC rushes material as part of the TRECVID 2007 evaluations. The method consists of initial shot boundary detection followed by shot similarity assessment and pruning, with both stages implemented using multiple parallel Self-Organizing Maps and within our content-based multimedia information retrieval and analysis framework named PicSOM. The results indicate that our approach can be successfully applied to rushes summarization. Compared to other submissions, our method resulted in the overall shortest summaries with close to median performance in the fraction of ground-truth inclusions found.