ABSTRACT
With the rapidly increasing rate of user-generated videos over the World Wide Web, it becoming a high necessity for users to navigate through them efficiently. Video summarization is considered to be one of the promising and effective approach for efficacious realization of video content by means of identifying and selecting descriptive frames of the video. In this paper, a proposed adaptive framework called Smart-Trailer (S-Trailer) is introduced to automatize the process of creating a movie trailer for any movie through its associated subtitles only. The proposed framework utilizes only English subtitles to be the language of usage. S-Trailer resolves the subtitle file to extract meaningful textual features that used to classify the movie into its corresponding genre(s). Experimentations on real movies showed that the proposed framework returns a considerable classification accuracy rate (0.89) to classify movies into their associated genre(s). The introduced framework generates an automated trailer that contains on average about (43%) accuracy in terms of recalling same scenes issued on the original movie trailer.
- iMovie - Apple. https://www.apple.com/lae/imovie/Google Scholar
- Windows Movie Maker https://www.windowsmovie-maker.org/Google Scholar
- Movie Trailer Maker---How to Make a Movie Trailer Movavi. https://www.movavi.com/support/how-to/how-tomake-a- movie-trailer.html.Google Scholar
- Create Your Own Movie Trailer With Our Online Video Maker."https://www.makewebvideo.com/en/make/movie-trailervideo.Google Scholar
- The Independent. "We spoke to the people who make film trailers " 17 Jan. 2017, http://www.independent.co.uk/artsentertainment/films/features/film-trailers-editors-interviewcreate-teasers-tv-spots-a7531076.html.Google Scholar
- A. Pavel, C. Reed, B. Hartmann, and B. Hartmann, Video dig ests: a browsable, skimmable format for informational lecture videos, in UISTUser Interface Software and Technology, SIGGRAPH ACM Special Interest Group on Computer Graphics and Interactive Techniques. NY, USA: ACM New York, October 2014, pp. 573--582. Google ScholarDigital Library
- Z. Xu and Y. Zhang, Automatic generated recommendation for movie trailers, in Broadband Multimedia Systems and Broadcasting (BMSB), 5-7 June 2013, London, UK. IEEE, October 2013. {OnlineGoogle ScholarCross Ref
- Ying Ding, et.al. PageRank for Ranking Authors in Co-citation Networks. JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, 60(11):2229--2243, 2009 Google ScholarDigital Library
- K. Bougiatiotis and T. Giannakopoulos, Content representation and similarity of movies based on topic extraction from subtitles, in SETN 16 Proceedings of the 9th Hellenic Conference on Artificial Intelligence, May 18 - 20, 2016, Google ScholarDigital Library
- R. Ren, H. Misra, and J. Jose. Semantic based adaptive movie summarization. In S. Boll, Q. Tian, L. Zhang, Z. Zhang, and Y.-P. Chen, editors, Advances in Multimedia Modeling, volume 5916 of Lecture Notes in Computer Science, pages 389-399.Springer Berlin Heidelberg, 2010. Google ScholarDigital Library
- J. Nessel and B. Cimpa, The movieoracle - content based movie recommendations, in Web Intelligence and Intelligent Agent Technology (WI-IAT), 2011 IEEE/WIC/ACM International Conference on, 22-27 Aug.2011, Lyon, France. IEEE, October 2011. Google ScholarDigital Library
- G. Irie, T. Satou, A. Kojima, T. Yamasaki, and K. Aizawa, Automatic trailer generation, in MM 10 Proceedings of the 18th ACM international conference on Multimedia, Firenze, Italy, SIGMULTIMEDIA ACM Special Interest Group on Multimedia. ACM New York, NY, October 2010, pp. 839--842 Google ScholarDigital Library
- H. Zhou, T. Hermans, A. V. Karandikar, and J. M. Rehg, Movie genre classification via scene categorization, in MM 10 Proceedings of the 18th ACM international conference on Multimedia, October 25 - 29, 2010, Firenze, Italy, SIGMULTIMEDIA ACM Special Interest Group on Multimedia. New York, USA: ACM New York, NY, October 2010, pp. 747--750 Google ScholarDigital Library
- A. F. Smeaton, B. Lehane, N. E. OConnor, C. Brady, and G. Craig, Automatically selecting shots for action movie trailers, in MIR 06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval, Santa Barbara, California, USA, SIGGRAPH ACM Special Interest Group on Computer Graphics and Interactive Techniques. New York, USA: ACM New York, NY, October 2006, pp. 231--238 Google ScholarDigital Library
- www.imdb.com/Google Scholar
- Hulth, A.: Improved automatic keyword extraction given more linguistic knowledge. In: Collins, M., Steedman, M. (eds.) Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing, pp. 216--223 (2003). Google ScholarDigital Library
- Wan, X., Xiao, J.: Single document keyphrase extraction using neighborhood knowledge. In: Proceedings of the 23rd National Conference on Artificial intelligence, AAAI 2008, vol. 2, pp. 855--860. AAAI Press (2008) Google ScholarDigital Library
- Eslam Amer. Enhancing Efficiency of Web Search Engines through Ontology Learning from unstructured information sources, Proceeding of 16th IEEE International conference of Information Integration and Reuse (IRI2015), PP.542--549, 13-15 August 2015. San Francisco, USA. Google ScholarDigital Library
- Youssif, Aliaa AA, Atef Z. Ghalwash, and Eslam A. Amer. "HSWS: Enhancing efficiency of web search engine via semantic web." In Proceedings of the International Conference on Management of Emergent Digital EcoSystems, pp. 212--219. ACM, 2011. Google ScholarDigital Library
- Aliaa A.A. Youssif, Atef Z. Ghalwash, and Eslam Amer. KPE: An Automatic Keyphrase Extraction Algorithm, Proceeding of IEEE International Conference on Information Systems and Computational Intelligence (ICISCI 2011), pp. 103--107, 2011.Google Scholar
- "Kaggle." https://www.kaggle.com/Google Scholar
- Eslam Amer, and Khaled Foad. "Akea: an Arabic keyphrase extraction algorithm." In International Conference on Advanced Intelligent Systems and Informatics, pp. 137--146. Springer, Cham, 2016Google Scholar
- Mohammed Hesham, Bishoy Hany, Nour Foad, and Eslam Amer. " Smart Trailer: Automatic generation of movie trailer using only subtitles." The First International Workshop on Deep and Representation Learning, IWDRL 2018. PP.26--30. IEEE, 2018Google Scholar
Index Terms
- A Framework to Automate the generation of movies' trailers using only subtitles
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