Related papers: GameVibe: A Multimodal Affective Game Corpus
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…
People are sharing their opinions, stories and reviews through online video sharing websites every day. Studying sentiment and subjectivity in these opinion videos is experiencing a growing attention from academia and industry. While…
Affective video indexing is the area of research that develops techniques to automatically generate descriptions of video content that encode the emotional reactions which the video content evokes in viewers. This paper provides a set of…
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 computing, through the lens of the four core phases of the…
Although media content is increasingly produced, distributed, and consumed in multiple combinations of modalities, how individual modalities contribute to the perceived emotion of a media item remains poorly understood. In this paper we…
To open up new possibilities to assess the multimodal perceptual quality of omnidirectional media formats, we proposed a novel open source 360 audiovisual (AV) quality dataset. The dataset consists of high-quality 360 video clips in…
Serious games are accepted as an effective approach to deliver augmented feedback in motor (re-) learning processes. The multi-modal nature of the conventional computer games (e.g. audiovisual representation) plus the ability to interact…
The development of video game streaming has grown rapidly, with major platforms such as YouTube and Twitch using different codecs. To support quality assessment models that work consistently across any codec, it is necessary to have access…
Is it possible to predict the affect of a user just by observing her behavioral interaction through a video? How can we, for instance, predict a user's arousal in games by merely looking at the screen during play? In this paper we address…
Humans use a host of signals to infer the emotional state of others. In general, computer systems that leverage signals from multiple modalities will be more robust and accurate in the same task. We present a multimodal affect and context…
Understanding affective dynamics in real-world social systems is fundamental to modeling and analyzing human-human interactions in complex environments. Group affect emerges from intertwined human-human interactions, contextual influences,…
This paper explores the use of visual effects common in video games that support a range of tasks that are similar in many ways to analysis tasks supported in visual analytics tools. While some visual effects are meant to increase…
Adaptive game systems aim to enrich player experiences by dynamically adjusting game content in response to user data. While extensive research has addressed content personalization and player experience modeling, the integration of these…
Quantitative analysis of Game User eXperience (GUX) is important to the game industry. Different from the typical questionnaire analysis, this paper focuses on the computational analysis of GUX. We aim to analyze the relationship between…
(arXiv abridged abstract) In the last two decades, videogames have evolved in a nearly explosive way from the pixelated graphics to today's near-realistic 3D environments. The interaction devices traditionally used in videogames have not…
Multimodal affective computing analyzes user-generated social media content to predict emotional states. However, a critical gap remains in understanding how visual content shapes cognitive interpretations and elicits specific affective…
The continuous improvement of human-computer interaction technology makes it possible to compute emotions. In this paper, we introduce our submission to the CVPR 2023 Competition on Affective Behavior Analysis in-the-wild (ABAW). Sentiment…
$\textit{BrainForm}$ is a gamified Brain-Computer Interface (BCI) training system designed for scalable data collection using consumer hardware and a minimal setup. We investigated (1) how users develop BCI control skills across repeated…
We present AMIGOS-- A dataset for Multimodal research of affect, personality traits and mood on Individuals and GrOupS. Different to other databases, we elicited affect using both short and long videos in two social contexts, one with…
From a computational viewpoint, emotions continue to be intriguingly hard to understand. In research, direct, real-time inspection in realistic settings is not possible. Discrete, indirect, post-hoc recordings are therefore the norm. As a…