A computational model for mood recognition

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

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

9 Citations (Scopus)
1 Downloads (Pure)

Abstract

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%.
Original languageEnglish
Title of host publicationProceedings of the 22nd International Conference on User Modeling, Adaptation and Personalization (UMAP), 7-11 July 2014, Aalborg, Denmark
Place of PublicationBerlin
PublisherSpringer
Pages122-133
ISBN (Print)978-3-319-08785-6
DOIs
Publication statusPublished - 2014
Event22nd International Conference on User Modeling, Adaptation and Personalization (UMAP 2014) - Aalborg, Denmark
Duration: 1 Jan 2014 → …
Conference number: 22

Conference

Conference22nd International Conference on User Modeling, Adaptation and Personalization (UMAP 2014)
Abbreviated titleUMAP 2014
CountryDenmark
CityAalborg
Period1/01/14 → …

Cite this