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Film clips retrieval using image queries

  • Ling ZouEmail author
  • Xin Jin
  • Bo Wei
Article

Abstract

The emergence of entertainment industry motivates the explosive growth of automatically film trailer. Manually finding desired clips from these large amounts of films is time-consuming and tedious, which makes finding the moments of user major or special preference becomes an urgent problem. Moreover, the user subjectivity over a film makes no fixed trailer caters to all tastes. This paper addresses these problems by posing a query-related film clip extraction framework which optimizes selected frames not only meet the semantic meaning of the queries but also have visual similarity on appearance between the query and selected clips. The experimental results show that our query-related film clip retrieval method is particularly useful for film editing, e.g. automatically finding movie clips to arouse audiences’ interests on the film.

Keywords

Deep learning Transfer learning Film editing 

Notes

Acknowledgments

The research was supported in part by the Natural Science Foundation of China (NSFC) under Grant No. 61703046 and open projects of state key laboratory of virtual reality technology and systems (No. BUAA-VR-17KF-05).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Digital Media SchoolBeijing Film AcademyBeijingChina
  2. 2.Beijing Electronic Science and Technology InstituteBeijingChina
  3. 3.Hangzhou dianzi UniversityZhejiangChina

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