Mining emotional features of movies

Yang Liu, Zhonglei Gu, Yu Zhang, Yan Liu

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

5 Citations (Scopus)

Abstract

In this paper, we present the algorithm designed for mining emotional features of movies. The algorithm dubbed Arousal-Valence Discriminant Preserving Embedding (AV-DPE) is proposed to extract the intrinsic features embedded in movies that are essentially differentiating in both arousal and valence directions. After dimensionality reduction, we use the neural network and support vector regressor to make the final prediction. Experimental results show that the extracted features can capture most of the discriminant information in movie emotions.

Original languageEnglish
Title of host publicationWorking Notes Proceedings of the MediaEval 2016 Workshop
EditorsGuillaume Gravier, Claire-Hélène Demarty, Hervé Bredin, Bogdan Ionescu, Christina Boididou, Emmanuel Dellandrea, Jaeyong Choi, Michael Riegler , Richard Sutcliffe, Igor Szoke, Gareth J. F. Jones, Martha Larson
PublisherCEUR-WS
Number of pages3
Publication statusPublished - 22 Nov 2016
Event2016 Multimedia Benchmark Workshop, MediaEval 2016 - Hilversum, Netherlands
Duration: 20 Oct 201621 Oct 2016
https://ceur-ws.org/Vol-1739/

Publication series

NameCEUR Workshop Proceedings
PublisherCEUR-WS
Volume1739
ISSN (Print)1613-0073

Conference

Conference2016 Multimedia Benchmark Workshop, MediaEval 2016
Country/TerritoryNetherlands
CityHilversum
Period20/10/1621/10/16
Internet address

Scopus Subject Areas

  • Computer Science(all)

Fingerprint

Dive into the research topics of 'Mining emotional features of movies'. Together they form a unique fingerprint.

Cite this