Advanced Motion Prediction for Virtual Reality Gaming: a CNN-Based Approach

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dc.contributor.authorJegierski, Huberten_US
dc.contributor.authorJegierski, Maciejen_US
dc.contributor.authorŁapczyński, Adrianen_US
dc.contributor.authorBabiuch, Pawełen_US
dc.contributor.authorPłaza, Mirosławen_US
dc.contributor.authorPięta, Pawełen_US
dc.contributor.authorŁukawski, Grzegorzen_US
dc.contributor.authorDeniziak, Stanisławen_US
dc.contributor.authorOpałka, Jaceken_US
dc.contributor.authorJasiński, Arturen_US
dc.contributor.authorIgras-Cybulska, Magdalenaen_US
dc.contributor.authorWęgrzyn, Pawełen_US
dc.contributor.editorTanabe, Takeshien_US
dc.contributor.editorYem, Vibolen_US
dc.date.accessioned2024-11-29T06:37:41Z
dc.date.available2024-11-29T06:37:41Z
dc.date.issued2024
dc.description.abstractA novel motion prediction model (MPM) for virtual reality (VR) video games was developed, consisting of a motion recognition model (MRM) and a next movement prediction model (NMPM), both using convolutional neural networks (CNNs). Motion capture was performed with HTC Vive Pro and Meta Quest 2. Two custom datasets were created to train the MRM and NMPM. Our method achieved a top-1 accuracy of 77% and a top-2 accuracy of 90%, even with motion data sequences sharing similar initial stages but diverging in subsequent movements.en_US
dc.description.sectionheadersPosters
dc.description.seriesinformationICAT-EGVE 2024 - International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments - Posters and Demos
dc.identifier.doi10.2312/egve.20241379
dc.identifier.isbn978-3-03868-246-2
dc.identifier.issn1727-530X
dc.identifier.pages2 pages
dc.identifier.urihttps://doi.org/10.2312/egve.20241379
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/egve20241379
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies → Virtual reality; Neural networks; Hardware → Sensor devices and platforms
dc.subjectComputing methodologies → Virtual reality
dc.subjectNeural networks
dc.subjectHardware → Sensor devices and platforms
dc.titleAdvanced Motion Prediction for Virtual Reality Gaming: a CNN-Based Approachen_US
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