activity
20192026
most citedPREFAB: PREFerence-based Affective Modeling for Low-Budget Self-Annotation

1 citations · 1 across the 5 of their papers we have counts for

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cs.HC2023

Affective Game Computing: A Survey

Georgios N. Yannakakis, David Melhart

This paper surveys the current state of the art in affective computing principles, methods and tools as applied to games. We review this emerging field, namely affective game compu…

cs.HC2023

The Ethics of AI in Games

David Melhart, Julian Togelius, Benedikte Mikkelsen +2

Video games are one of the richest and most popular forms of human-computer interaction and, hence, their role is critical for our understanding of human behaviour and affect at a…

cs.HC2021

Towards General Models of Player Experience: A Study Within Genres

David Melhart, Antonios Liapis, Georgios N. Yannakakis

To which degree can abstract gameplay metrics capture the player experience in a general fashion within a game genre? In this comprehensive study we address this question across th…

cs.HC2021

Privileged Information for Modeling Affect In The Wild

Konstantinos Makantasis, David Melhart, Antonios Liapis +1

A key challenge of affective computing research is discovering ways to reliably transfer affect models that are built in the laboratory to real world settings, namely in the wild.…

cs.HC2020

Moment-to-moment Engagement Prediction through the Eyes of the Observer: PUBG Streaming on Twitch

David Melhart, Daniele Gravina, Georgios N. Yannakakis

Is it possible to predict moment-to-moment gameplay engagement based solely on game telemetry? Can we reveal engaging moments of gameplay by observing the way the viewers of the ga…

cs.HC2019

PAGAN: Video Affect Annotation Made Easy

David Melhart, Antonios Liapis, Georgios N. Yannakakis

How could we gather affect annotations in a rapid, unobtrusive, and accessible fashion? How could we still make sure that these annotations are reliable enough for data-hungry affe…