An agglomerative approach for shot summarization based on content homogeneity

Antonis Ioannidis; Vasileios Chasanis; Aristidis Likas

doi:10.1117/12.2180531

14 February 2015 An agglomerative approach for shot summarization based on content homogeneity

Antonis Ioannidis, Vasileios Chasanis, Aristidis Likas

Proceedings Volume 9445, Seventh International Conference on Machine Vision (ICMV 2014); 94451F (2015) https://doi.org/10.1117/12.2180531
Event: Seventh International Conference on Machine Vision (ICMV 2014), 2014, Milan, Italy

Abstract

An efficient shot summarization method is presented based on agglomerative clustering of the shot frames. Unlike other agglomerative methods, our approach relies on a cluster merging criterion that computes the content homogeneity of a merged cluster. An important feature of the proposed approach is the automatic estimation of the number of a shot's most representative frames, called keyframes. The method starts by splitting each video sequence into small, equal sized clusters (segments). Then, agglomerative clustering is performed, where from the current set of clusters, a pair of clusters is selected and merged to form a larger unimodal (homogeneous) cluster. The algorithm proceeds until no further cluster merging is possible. At the end, the medoid of each of the final clusters is selected as keyframe and the set of keyframes constitutes the summary of the shot. Numerical experiments demonstrate that our method reasonable estimates the number of ground-truth keyframes, while extracting non-repetitive keyframes that efficiently summarize the content of each shot.

Citation Download Citation

Antonis Ioannidis, Vasileios Chasanis, and Aristidis Likas "An agglomerative approach for shot summarization based on content homogeneity", Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 94451F (14 February 2015); https://doi.org/10.1117/12.2180531

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