Video summarization via block sparse dictionary selection

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

64 Scopus Citations
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  • Mingyang Ma
  • Shaohui Mei
  • Shuai Wan
  • Zhiyong Wang
  • David Dagan Feng

Related Research Unit(s)


Original languageEnglish
Pages (from-to)197-209
Journal / PublicationNeurocomputing
Online published23 Oct 2019
Publication statusPublished - 22 Feb 2020


The explosive growth of video data has raised new challenges for many video processing tasks such as video browsing and retrieval, hence, effective and efficient video summarization (VS) is urgently demanded to automatically summarize a video into a succinct version. Recent years have witnessed the advancements of sparse representation based approaches for VS. However, video frames are analyzed individually for keyframe selection in existing methods, which could lead to redundancy among selected keyframes and poor robustness to outlier frames. Due to that adjacent frames are visually similar, candidate keyframes often occur in temporal blocks, in addition to sparse presence. Therefore, in this paper, the block-sparsity of candidate keyframes is taken into consideration, by which the VS problem is formulated as a block sparse dictionary selection model. Moreover, a simultaneous block version of Orthogonal Matching Pursuit (SBOMP) algorithm is designed for model optimization. Two keyframe selection strategies are also explored for each block. Experimental results on two benchmark datasets, namely VSumm and TVSum datasets, demonstrate that the proposed SBOMP based VS method clearly outperforms several state-of-the-art sparse representation based methods in terms of F-score, redundancy among keyframes and robustness to outlier frames.

Research Area(s)

  • Block-sparsity, Video summarization, Sparse representation, Dictionary selection

Citation Format(s)

Video summarization via block sparse dictionary selection. / Ma, Mingyang; Mei, Shaohui; Wan, Shuai et al.
In: Neurocomputing, Vol. 378, 22.02.2020, p. 197-209.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review