Label-Free Subjective Player Experience Modelling via Let's Play Videos
Fuente:
arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866910632193818624 |
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| author | Goel, Dave Mahmoudi-Nejad, Athar Guzdial, Matthew |
| author_facet | Goel, Dave Mahmoudi-Nejad, Athar Guzdial, Matthew |
| contents | Player Experience Modelling (PEM) is the study of AI techniques applied to modelling a player's experience within a video game. PEM development can be labour-intensive, requiring expert hand-authoring or specialized data collection. In this work, we propose a novel PEM development approach, approximating player experience from gameplay video. We evaluate this approach predicting affect in the game Angry Birds via a human subject study. We validate that our PEM can strongly correlate with self-reported and sensor measures of affect, demonstrating the potential of this approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_02967 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Label-Free Subjective Player Experience Modelling via Let's Play Videos Goel, Dave Mahmoudi-Nejad, Athar Guzdial, Matthew Human-Computer Interaction Artificial Intelligence Machine Learning Player Experience Modelling (PEM) is the study of AI techniques applied to modelling a player's experience within a video game. PEM development can be labour-intensive, requiring expert hand-authoring or specialized data collection. In this work, we propose a novel PEM development approach, approximating player experience from gameplay video. We evaluate this approach predicting affect in the game Angry Birds via a human subject study. We validate that our PEM can strongly correlate with self-reported and sensor measures of affect, demonstrating the potential of this approach. |
| title | Label-Free Subjective Player Experience Modelling via Let's Play Videos |
| topic | Human-Computer Interaction Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2410.02967 |