A computational model for mood recognition

C. Katsimerou, J.A. Redi, I.E.J. Heynderickx

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

9 Citaten (Scopus)
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Samenvatting

Abstract In an ambience designed to adapt to the user’s affective state, pervasive technology should be able to decipher unobtrusively his underlying mood. Great effort has been devoted to automatic punctual emotion recognition from visual input. Conversely, little has been done to recognize longer-lasting affective states, such as mood. Taking for granted the effectiveness of emotion recognition algorithms, we go one step further and propose a model for estimating the mood of an affective episode from a known sequence of punctual emotions. To validate our model experimentally, we rely on the human annotations of the well-established HUMAINE database. Our analysis indicates that we can approximate fairly accurately the human process of summarizing the emotional content of a video in a mood estimation. A moving average function with exponential discount of the past emotions achieves mood prediction accuracy above 60%.
Originele taal-2Engels
TitelProceedings of the 22nd International Conference on User Modeling, Adaptation and Personalization (UMAP), 7-11 July 2014, Aalborg, Denmark
Plaats van productieBerlin
UitgeverijSpringer
Pagina's122-133
ISBN van geprinte versie978-3-319-08785-6
DOI's
StatusGepubliceerd - 2014
Evenement22nd International Conference on User Modeling, Adaptation and Personalization (UMAP 2014) - Aalborg, Denemarken
Duur: 1 jan 2014 → …
Congresnummer: 22

Congres

Congres22nd International Conference on User Modeling, Adaptation and Personalization (UMAP 2014)
Verkorte titelUMAP 2014
LandDenemarken
StadAalborg
Periode1/01/14 → …
Ander22nd International Conference on User Modeling, Adaptation and Personalization (UMAP)

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