LATIDIA · Investigación

Reconocimiento de gestos manuales en tiempo real para OpenXR mediante aprendizaje automático basado en transformadores

arXiv:2609.25466v1 Tipo de anuncio: nuevo Resumen: El reconocimiento de gestos con las manos es un componente clave en la interacción persona-ordenador (HCI), que permite interfaces intuitivas para aplicaciones en juegos, realidad virtual (VR), robótica,

La noticia

arXiv:2609.25466v1 Announce Type: new Abstract: Hand gesture recognition is a key component in human-computer interaction (HCI), enabling intuitive interfaces for applications in gaming, virtual reality (VR), robotics, and more. This study integrates transformer-based machine-learning models for real-time hand gesture recognition, using hand-tracking data captured through the OpenXR standard in Unity. We leverage positional data of hand joints and wrist rotation angles to train a custom gesture recognition system. By utilizing the sequential modeling capabilities of transformers, the system captures temporal dependencies within short gesture windows and classifies gestures robustly across hand orientations and sizes. The results show a significant improvement in gesture classification accuracy. Building on this, we outline how