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The Arousal Video Game AnnotatIoN (AGAIN) Dataset.

Authors :
Melhart, David
Liapis, Antonios
Yannakakis, Georgios N.
Source :
IEEE Transactions on Affective Computing; Oct-Dec2022, Vol. 13 Issue 14, p2171-2184, 14p
Publication Year :
2022

Abstract

How can we model affect in a general fashion, across dissimilar tasks, and to which degree are such general representations of affect even possible? To address such questions and enable research towards general affective computing, this paper introduces The Arousal video Game AnnotatIoN (AGAIN) dataset. AGAIN is a large-scale affective corpus that features over 1,100 in-game videos (with corresponding gameplay data) from nine different games, which are annotated for arousal from 124 participants in a first-person continuous fashion. Even though AGAIN is created for the purpose of investigating the generality of affective computing across dissimilar tasks, affect modelling can be studied within each of its 9 specific interactive games. To the best of our knowledge AGAIN is the largest—over 37 hours of annotated video and game logs—and most diverse publicly available affective dataset based on games as interactive affect elicitors. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19493045
Volume :
13
Issue :
14
Database :
Complementary Index
Journal :
IEEE Transactions on Affective Computing
Publication Type :
Academic Journal
Accession number :
160689521
Full Text :
https://doi.org/10.1109/TAFFC.2022.3188851