Work in Progress

A Web Service for Video Summarization

Authors:

Chrysa Collyda,

Konstantinos Apostolidis,

Evlampios Apostolidis,

Eleni Adamantidou,

Alexandros I. Metsai,

Vasileios MezarisAuthors Info & Claims

IMX '20: Proceedings of the 2020 ACM International Conference on Interactive Media Experiences

Pages 148 - 153

https://doi.org/10.1145/3391614.3399391

Published: 17 June 2020 Publication History

Abstract

This paper presents a Web service that supports the automatic generation of video summaries for user-submitted videos. The developed Web application decomposes the video into segments, evaluates the fitness of each segment to be included in the video summary and selects appropriate segments until a pre-defined time budget is filled. The integrated deep-learning-based video analysis and summarization technologies exhibit state-of-the-art performance and, by exploiting the processing capabilities of modern GPUs, offer faster than real-time processing. Configurations for generating video summaries that fulfill the specifications for posting on the most common video sharing platforms and social networks are available in the user interface of this application, enabling the one-click generation of distribution-channel-specific summaries.

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Cited By

Apostolidis EBalaouras GPatras IMezaris V(2024)Explainable Video Summarization for Advancing Media Content ProductionEncyclopedia of Information Science and Technology, Sixth Edition10.4018/978-1-6684-7366-5.ch065(1-24)Online publication date: 1-Jul-2024
https://doi.org/10.4018/978-1-6684-7366-5.ch065
Nixon LApostolidis KApostolidis EGalanopoulos DMezaris VPhilipp BBocyte R(2024)AI and data-driven media analysis of TV content for optimised digital content marketingMultimedia Systems10.1007/s00530-023-01195-730:1Online publication date: 19-Jan-2024
https://doi.org/10.1007/s00530-023-01195-7
Apostolidis EApostolidis KMezaris V(2024)Facilitating the Production of Well-Tailored Video Summaries for Sharing on Social MediaMultiMedia Modeling10.1007/978-3-031-53302-0_21(271-278)Online publication date: 29-Jan-2024
https://doi.org/10.1007/978-3-031-53302-0_21
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cover image ACM Conferences

IMX '20: Proceedings of the 2020 ACM International Conference on Interactive Media Experiences

June 2020

211 pages

ISBN:9781450379762

DOI:10.1145/3391614

Copyright © 2020 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

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Publication History

Published: 17 June 2020

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H2020 LEIT Information and Communication Technologies

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IMX '20

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IMX '20: ACM International Conference on Interactive Media Experiences

June 17 - 19, 2020

Cornella, Barcelona, Spain

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Overall Acceptance Rate 69 of 245 submissions, 28%

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IMX '25

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ACM International Conference on Interactive Media Experiences

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Cited By

Apostolidis EBalaouras GPatras IMezaris V(2024)Explainable Video Summarization for Advancing Media Content ProductionEncyclopedia of Information Science and Technology, Sixth Edition10.4018/978-1-6684-7366-5.ch065(1-24)Online publication date: 1-Jul-2024
https://doi.org/10.4018/978-1-6684-7366-5.ch065
Nixon LApostolidis KApostolidis EGalanopoulos DMezaris VPhilipp BBocyte R(2024)AI and data-driven media analysis of TV content for optimised digital content marketingMultimedia Systems10.1007/s00530-023-01195-730:1Online publication date: 19-Jan-2024
https://doi.org/10.1007/s00530-023-01195-7
Apostolidis EApostolidis KMezaris V(2024)Facilitating the Production of Well-Tailored Video Summaries for Sharing on Social MediaMultiMedia Modeling10.1007/978-3-031-53302-0_21(271-278)Online publication date: 29-Jan-2024
https://doi.org/10.1007/978-3-031-53302-0_21
Apostolidis EMezaris VPatras IKankanhalli MPatras ILiu JWong YKomamizu T(2023)A Study on the Use of Attention for Explaining Video SummarizationProceedings of the 2nd Workshop on User-centric Narrative Summarization of Long Videos10.1145/3607540.3617138(41-49)Online publication date: 29-Oct-2023
https://dl.acm.org/doi/10.1145/3607540.3617138
Nixon LFoss JApostolidis KMezaris V(2022)Data-driven personalisation of television content: a surveyMultimedia Systems10.1007/s00530-022-00926-628:6(2193-2225)Online publication date: 1-Dec-2022
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Nixon LApostolidis KApostolidis EGalanopoulos DMezaris VPhilipp BBocyte R(2021)Content Wizard: demo of a trans-vector digital video publication toolProceedings of the 2021 ACM International Conference on Interactive Media Experiences10.1145/3452918.3468083(296-298)Online publication date: 21-Jun-2021
https://dl.acm.org/doi/10.1145/3452918.3468083
Apostolidis EAdamantidou EMetsai AMezaris VPatras I(2021)Video Summarization Using Deep Neural Networks: A SurveyProceedings of the IEEE10.1109/JPROC.2021.3117472109:11(1838-1863)Online publication date: Nov-2021
https://doi.org/10.1109/JPROC.2021.3117472
Apostolidis KMezaris V(2021)A Web Service for Video Smart-Cropping2021 IEEE International Symposium on Multimedia (ISM)10.1109/ISM52913.2021.00011(25-26)Online publication date: Nov-2021
https://doi.org/10.1109/ISM52913.2021.00011

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