Feature selection in multimodal continuous emotion prediction

Shahin Amiriparian, Michael Freitag, Nicholas Cummins, Björn Schuller

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

Advances in affective computing have been made by combining information from different modalities, such as audio, video, and physiological signals. However, increasing the number of modalities also grows the dimensionality of the associated feature vectors, leading to higher computational cost and possibly lower prediction performance. In this regard, we present an comparative study of feature reduction methodologies for continuous emotion recognition. We compare dimensionality reduction by principal component analysis, filter-based feature selection using canonical correlation analysis, and correlation-based feature selection, as well as wrapper-based feature selection with sequential forward selection, and competitive swarm optimisation. These approaches are evaluated on the AV2015 database using support vector regression. Our results demonstrate that the wrapper-based approaches typically outperform the other methodologies, while pruning a large number of irrelevant features.

Original languageEnglish
Title of host publication2017 7th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages30-37
Number of pages8
ISBN (Electronic)9781538606803
DOIs
StatePublished - 2 Jul 2017
Event7th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2017 - San Antonio, United States
Duration: 23 Oct 201726 Oct 2017

Publication series

Name2017 7th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2017
Volume2018-January

Conference

Conference7th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2017
Country/TerritoryUnited States
CitySan Antonio
Period23/10/1726/10/17

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