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A Smooth Video Summarization Method Based on Frame-Filling

  • Xiaoyu Teng
  • , Xiaolin Gui
  • , Huijun Dai
  • , Tianjiao Du
  • , Zhenxing Wang
  • , Hui Li
  • Xi'an Jiaotong University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Given the existing video summarization algorithms have too much redundancy in video semantics, and destroy the maximum continuity between video frames, a smooth video summarization generation method is designed in this paper. This method is based on the video keyframe selection, which is mainly divided into three parts. In the first part, this method completes the de-redundancy operation based on the similarity calculated by the essential characteristics of the video frame. The second part completes the shot segmentation processing using the capsule network. The third part can be divided into two sub-parts, key frames selection and filling. The former of this part is selects key-frames based on video semantic, and the latter is smooths summarization based on frame-filling. Experimental results show that the video summarization algorithms designed in this paper can outperform several existing algorithms and achieve excellent results in terms of video content integrity, semantic accuracy and so on.

Original languageEnglish
Title of host publication2020 IEEE 20th International Conference on Communication Technology, ICCT 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1418-1422
Number of pages5
ISBN (Electronic)9781728181417
DOIs
StatePublished - 28 Oct 2020
Event20th IEEE International Conference on Communication Technology, ICCT 2020 - Nanning, China
Duration: 28 Oct 202031 Oct 2020

Publication series

NameInternational Conference on Communication Technology Proceedings, ICCT
Volume2020-October

Conference

Conference20th IEEE International Conference on Communication Technology, ICCT 2020
Country/TerritoryChina
CityNanning
Period28/10/2031/10/20

Keywords

  • de-redundancy
  • key-frames filling
  • video semantic
  • video summarization

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