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Computer Science > Computer Vision and Pattern Recognition

Title: Analysing the Memorability of a Procedural Crime-Drama TV Series, CSI

Abstract: We investigate the memorability of a 5-season span of a popular crime-drama TV series, CSI, through the application of a vision transformer fine-tuned on the task of predicting video memorability. By investigating the popular genre of crime-drama TV through the use of a detailed annotated corpus combined with video memorability scores, we show how to extrapolate meaning from the memorability scores generated on video shots. We perform a quantitative analysis to relate video shot memorability to a variety of aspects of the show. The insights we present in this paper illustrate the importance of video memorability in applications which use multimedia in areas like education, marketing, indexing, as well as in the case here namely TV and film production.
Comments: 7 pages, accepted to CBMI 2022
Subjects: Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI); Multimedia (cs.MM)
DOI: 10.1145/3549555.3549592
Cite as: arXiv:2208.03479 [cs.CV]
  (or arXiv:2208.03479v1 [cs.CV] for this version)

Submission history

From: Alan Smeaton [view email]
[v1] Sat, 6 Aug 2022 09:29:46 GMT (417kb,D)

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