Jegierski, HubertJegierski, MaciejŁapczyński, AdrianBabiuch, PawełPłaza, MirosławPięta, PawełŁukawski, GrzegorzDeniziak, StanisławOpałka, JacekJasiński, ArturIgras-Cybulska, MagdalenaWęgrzyn, PawełTanabe, TakeshiYem, Vibol2024-11-292024-11-292024978-3-03868-246-21727-530Xhttps://doi.org/10.2312/egve.20241379https://diglib.eg.org/handle/10.2312/egve20241379A 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.Attribution 4.0 International LicenseCCS Concepts: Computing methodologies → Virtual reality; Neural networks; Hardware → Sensor devices and platformsComputing methodologies → Virtual realityNeural networksHardware → Sensor devices and platforms10.2312/egve.202413792 pages