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Hierarchical Keyframe-based Video Summarization Using QR-Decomposition and Modified -Means Clustering


We propose a novel hierarchical keyframe-based video summarization system using QR-decomposition. Specially, we attend to the challenges of defining some measures to detect the dynamicity of a shot and video and extracting appropriate keyframes that assure the purity of video summary. We derive some efficient measures to compute the dynamicity of video shots using QR-decomposition, and we utilize it in detecting the number of keyframes that must be selected from each shot. Also, we derive a theorem that illustrates an important property of QR-decomposition. We utilize it in order to summarize video shots with low redundancy. The proposed algorithm is implemented and evaluated on TRECVID 2006 benchmark platform. Compared with other algorithms, our results are among the best.

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Correspondence to Ali Amiri.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Amiri, A., Fathy, M. Hierarchical Keyframe-based Video Summarization Using QR-Decomposition and Modified -Means Clustering. EURASIP J. Adv. Signal Process. 2010, 892124 (2010).

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