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Erschienen in:
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2021 | OriginalPaper | Buchkapitel

77. Multi-Class Classification of Actors in Movie Trailers

verfasst von : Prashant Giridhar Shambharkar, Gaurang Mehrotra, Kanishk Singh Thakur, Kaushal Thakare, Mohammad Nazmud Doja

Erschienen in: Proceedings of the International Conference on Paradigms of Computing, Communication and Data Sciences

Verlag: Springer Singapore

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Abstract

A trailer is a short version of the movie which gives the viewer information about the movie such as its genre, the cast and what the audience needs to expect from the movie. You should never judge a book by its cover but you can always judge a movie by its trailer. So in this paper, we aim to classify actors in movie trailers by extracting key frames from trailers and obtaining features from it through convolutional neural network and then classifying it using the output function. A trailer emphasises the type of movie it is marketing. Actors are one of the most important aspects in a movie and play a decisive role when analysing the overall popularity of the movie. A trailer always gives a sneak-peak of the actors that are going to play a crucial role in the movie. Recognising actors in a movie trailer thus becomes an important task as much of the viewer’s pre-judge a movie based on the actors that glorify its cast.

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Vorheriges Kapitel Image Filtering Using Fuzzy Rules and DWT-SVM for Tumor Identification
Nächstes Kapitel Analysis of Machine Learning and Deep Learning Approaches for DDoS Attack Detection on Internet of Things Network
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Metadaten
Titel
Multi-Class Classification of Actors in Movie Trailers
verfasst von
Prashant Giridhar Shambharkar
Gaurang Mehrotra
Kanishk Singh Thakur
Kaushal Thakare
Mohammad Nazmud Doja
Copyright-Jahr
2021
Verlag
Springer Singapore
Buch
Proceedings of the International Conference on Paradigms of Computing, Communication and Data Sciences

Print ISBN: 978-981-15-7532-7

Electronic ISBN: 978-981-15-7533-4

Copyright-Jahr: 2021

DOI
https://doi.org/10.1007/978-981-15-7533-4_77

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