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Hierarchical video summarization in reference subspace

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3 Author(s)
Jiang, R.M. ; Comput. Sci., Loughborough Univ., Loughborough, UK ; Sadka, A.H. ; Crookes, D.

In this paper, a hierarchical video structure summarization approach using Laplacian Eigenmap is proposed, where a small set of reference frames is selected from the video sequence to form a reference subspace to measure the dissimilarity between two arbitrary frames. In the proposed summarization scheme, the shot-level key frames are first detected from the continuity of inter-frame dissimilarity, and the sub-shot level and scene level representative frames are then summarized by using k-mean clustering. The experiment is carried on both test videos and movies, and the results show that in comparison with a similar approach using latent semantic analysis, the proposed approach using Laplacian Eigenmap can achieve a better recall rate in keyframe detection, and gives an efficient hierarchical summarization at sub shot, shot and scene levels subsequently.

Published in:

Consumer Electronics, IEEE Transactions on  (Volume:55 ,  Issue: 3 )

Date of Publication:

August 2009

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