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dc.contributor.author | Rehusevych, Orest![]() |
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dc.date.accessioned | 2024-02-14T15:39:11Z | |
dc.date.available | 2024-02-14T15:39:11Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Rehusevych, Orest. movie2trailer: Unsupervised trailer generation using Anomaly detection / Rehusevych, Orest; Supervisor: Taras Firman; Ukrainian Catholic University, Department of Computer Sciences. – Lviv: 2019. – 45 p. | uk |
dc.identifier.uri | https://er.ucu.edu.ua/handle/1/4472 | |
dc.language.iso | en | uk |
dc.title | movie2trailer: Unsupervised trailer generation using Anomaly detection | uk |
dc.type | Preprint | uk |
dc.status | Публікується вперше | uk |
dc.description.abstracten | In this work, we present a novel unsupervised approach for automatic trailer gen- eration - movie2trailer. To our knowledge, it is the first-ever application of anomaly detection to such a creative and challenging part of the trailer creation process as a shot selection. One of the main advantages of our approach over the competitors is that it does not require any prior knowledge and extracts all needed information directly from the input movie. By leveraging the recent advancements in video and audio analysis, we can produce high-quality movie trailers in equal or less time than professional movie editors. The proposed approach reaches state-of-the-art in terms of visual attractiveness and closeness to the "real" trailer. Moreover, it exposes new horizons for researching anomaly detection applications in the movie industry. An example of generated with our approach trailer for the movie "Requiem for a dream" can be observed on YouTube. | uk |