Article

Automatically selecting shots for action movie trailers

Authors:

Alan F. Smeaton,

Noel E. O'Connor,

Gary CraigAuthors Info & Claims

MIR '06: Proceedings of the 8th ACM international workshop on Multimedia information retrieval

Pages 231 - 238

https://doi.org/10.1145/1178677.1178709

Published: 26 October 2006 Publication History

Abstract

Movie trailers, or previews, are an important method of advertising movies. They are extensively shown before movies in cinemas, as well as on television and increasingly, over the Internet. Making a trailer is a creative process, in which a number of shots from a movie are selected in order to entice a viewer in to paying to see the full movie. Thus, the creation of these trailers is an integral part in the promotion of a movie. Action movies in particular rely on trailers as a form of advertising as it is possible to show short, exciting portions of an action movie, which are likely to appeal to the target audience. This paper presents an approach which automatically selects shots from action movies in order to assist in the creation of trailers. A set of audiovisual features are extracted that aim to model the characteristics of shots typically present in trailers, and a support vector machine is utilised in order to select the relevant shots. The approach taken is not particularly novel but the results show that the process may be used in order to ease the trailer creation process or to facilitate the creation of variable length, or personalised trailers.

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Cited By

Papalampidi PKeller FLapata M(2024)Finding the Right Moment: Human-Assisted Trailer Creation via Task CompositionIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2023.332303046:1(292-304)Online publication date: Jan-2024
https://doi.org/10.1109/TPAMI.2023.3323030
Balestri RCascarano PEsposti MPescatore G(2024)An Automatic Deep Learning Approach for Trailer Generation through Large Language Models2024 9th International Conference on Frontiers of Signal Processing (ICFSP)10.1109/ICFSP62546.2024.10785516(93-100)Online publication date: 12-Sep-2024
https://doi.org/10.1109/ICFSP62546.2024.10785516
Argaw DSoldan MPardo AZhao CHeilbron FChung JGhanem B(2024)Towards Automated Movie Trailer Generation2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.00711(7445-7454)Online publication date: 16-Jun-2024
https://doi.org/10.1109/CVPR52733.2024.00711
Show More Cited By

Index Terms

Automatically selecting shots for action movie trailers
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision

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Published In

cover image ACM Conferences

MIR '06: Proceedings of the 8th ACM international workshop on Multimedia information retrieval

October 2006

344 pages

ISBN:1595934952

DOI:10.1145/1178677

General Chairs:
James Z. Wang
The Pennsylvania State University
,
Nozha Boujemaa
INRIA Rocquencourt, France
,
Yixin Chen
The University of Mississippi

Copyright © 2006 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 26 October 2006

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MM06: The 14th ACM International Conference on Multimedia 2006

October 26 - 27, 2006

California, Santa Barbara, USA

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Cited By

Papalampidi PKeller FLapata M(2024)Finding the Right Moment: Human-Assisted Trailer Creation via Task CompositionIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2023.332303046:1(292-304)Online publication date: Jan-2024
https://doi.org/10.1109/TPAMI.2023.3323030
Balestri RCascarano PEsposti MPescatore G(2024)An Automatic Deep Learning Approach for Trailer Generation through Large Language Models2024 9th International Conference on Frontiers of Signal Processing (ICFSP)10.1109/ICFSP62546.2024.10785516(93-100)Online publication date: 12-Sep-2024
https://doi.org/10.1109/ICFSP62546.2024.10785516
Argaw DSoldan MPardo AZhao CHeilbron FChung JGhanem B(2024)Towards Automated Movie Trailer Generation2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.00711(7445-7454)Online publication date: 16-Jun-2024
https://doi.org/10.1109/CVPR52733.2024.00711
Bretti CMettes PKoops HOdijk Dvan Noord N(2024)Find the Cliffhanger: Multi-modal Trailerness in Soap OperasMultiMedia Modeling10.1007/978-3-031-53308-2_15(199-212)Online publication date: 28-Jan-2024
https://doi.org/10.1007/978-3-031-53308-2_15
Wang ZLi JJiang Y(2021)Story-driven Video EditingIEEE Transactions on Multimedia10.1109/TMM.2020.303746123(4027-4036)Online publication date: 2021
https://doi.org/10.1109/TMM.2020.3037461
Gaikwad BSontakke APatwardhan MPedanekar NKarande S(2021)Plots to Previews: Towards Automatic Movie Preview Retrieval using Publicly Available Meta-data2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)10.1109/ICCVW54120.2021.00359(3198-3207)Online publication date: Oct-2021
https://doi.org/10.1109/ICCVW54120.2021.00359
Mujtaba GRyu E(2020)Client-Driven Personalized Trailer Framework Using Thumbnail ContainersIEEE Access10.1109/ACCESS.2020.29829928(60417-60427)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2982992
Bost XGueye SLabatut VLarson MLinarès GMalinas DRoth R(2019)Remembering winter was comingMultimedia Tools and Applications10.1007/s11042-019-07969-4Online publication date: 3-Sep-2019
https://doi.org/10.1007/s11042-019-07969-4
Sheng JChen YLi YLi L(2018)Embedded learning for computerized production of movie trailersMultimedia Tools and Applications10.5555/3288251.328831377:22(29347-29365)Online publication date: 1-Nov-2018
https://dl.acm.org/doi/10.5555/3288251.3288313
Amer ENabil A(2018)A Framework to Automate the generation of movies' trailers using only subtitlesProceedings of the 7th International Conference on Software and Information Engineering10.1145/3220267.3220293(126-130)Online publication date: 2-May-2018
https://dl.acm.org/doi/10.1145/3220267.3220293
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