Adaptive key frame extraction using unsupervised clustering

Published 27 November 2002

Yueting Zhuang, Yong Rui, Thomas S. Huang, Sharad Mehrotra

DOI10.1109/icip.1998.723655

Citations507

TL;DR

A new algorithm for key frame extraction based on unsupervised clustering is introduced, both computationally simple and able to adapt to the visual content, which is validated by large amount of real-world videos.

Abstract

Key frame extraction has been recognized as one of the important research issues in video information re-trieval. Although progress has been made in key frame extraction, the existing approaches are either compu-tationally expensive or ineective in capturing salient visual content. In this paper, we rst discuss the im-portance of key frame selection; and then brie\ny review and evaluate the existing approaches. To overcome the shortcomings of the existing approaches, we introduce a new algorithm for key frame extraction based on un-supervised clustering. The proposed algorithm is both computationally simple and able to adapt to the visual content. The eciency and eectiveness are validated by large amount of real-world videos. 1.

Keywords

Computer Science

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