Narrative videos usually illustrate the main content through multiple narrative information such as audios, video frames and subtitles. Existing video summarization approaches rarely consider the multiple dimensional narrative inputs, or ignore the impact of shots artistic assembly when directly applied to narrative videos. This paper introduces a multimodal-based and aesthetic-guided narrative video summarization method. Our method leverages multimodal information including visual content, subtitles and audio information through our specified key shots selection, subtitle summarization, and highlight extraction components. Furthermore, under the guidance of cinematographic aesthetic, we design a novel shots assembly module to ensure the shot content completeness and then assemble the selected shots into a desired summary. Besides, our method also provides the flexible specification for shots selection, to achieve which it automatically selects semantically related shots according to the user-designed text. By conducting a large number of quantitative experimental evaluations and user studies, we demonstrate that our method effectively preserves important narrative information of the original video, and it is capable of rapidly producing high-quality and aesthetic-guided narrative video summaries.

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IEEE Transactions on Multimedia
Centrum Wiskunde & Informatica, Amsterdam (CWI), The Netherlands

Xie, J, Chen, X, Zhang, T, Zhang, Y, Lu, S.-P, César Garcia, P.S, & Yang, Y. (2022). Multimodal-based and aesthetic-guided narrative video summarization. IEEE Transactions on Multimedia. doi:10.1109/TMM.2022.3183394