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| pub:research [2020/11/19 13:01] – [Prototypes of Affective Games] kkutt | pub:research [2021/01/07 10:19] – MRC2020 published kkutt | ||
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| === MRC2020 === | === MRC2020 === | ||
| - | * L. Żuchowska, K. Kutt, K. Geleta, S. Bobek, and G. J. Nalepa, " | + | * L. Żuchowska, K. Kutt, K. Geleta, S. Bobek, and G. J. Nalepa, " |
| - | * {{http://mrc.kriwi.de/2020/download/ | + | * {{http://ceur-ws.org/Vol-2787/paper7.pdf|Full text available online}} |
| * ++Abstract | We propose an experimental framework for Affective Computing based of video games. We developed a set of specially designed mini-games, based of carefully selected game mechanics, to evoke emotions of participants of a larger experiment. We believe, that games provide a controllable yet overall ecological environment for studying emotions. We discuss how we used our mini-games as an important counterpart of classical visual and auditory stimuli. Furthermore, | * ++Abstract | We propose an experimental framework for Affective Computing based of video games. We developed a set of specially designed mini-games, based of carefully selected game mechanics, to evoke emotions of participants of a larger experiment. We believe, that games provide a controllable yet overall ecological environment for studying emotions. We discuss how we used our mini-games as an important counterpart of classical visual and auditory stimuli. Furthermore, | ||
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| * Presented at [[pub: | * Presented at [[pub: | ||
| * {{http:// | * {{http:// | ||
| + | * ++Abstract | In this paper we discuss selected important challenges in designing experiments that lead to data and information collection on affective states of participants. We aim at acquiring data that would be basis to formulate and evaluate computer methods for detection, identification and interpretation of such affective states, and ultimately human emotions.++ | ||
| === AfCAI2016a === | === AfCAI2016a === | ||
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| * Presented at [[pub: | * Presented at [[pub: | ||
| * {{http:// | * {{http:// | ||
| + | * ++Abstract | We are aiming at developing a technology to detect, identify and interpret human emotional states. We believe, that it can be provided based on the integration of context-aware systems and affective computing paradigms. We are planning to identify and characterize affective context data, and provide knowledge-based models to identify and interpret affects based on this data. A working name for this technology is simply AfCAI: Affective Computing with Context Awareness for Ambient Intelligence.++ | ||
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| ===== Tools and Datasets ===== | ===== Tools and Datasets ===== | ||
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