Facial Feature Enhancement for Immersive Real-Time Avatar-Based Sign Language Communication using Personalized CNNs
Kristoffer Waldow, Arnulph Fuhrmann and Daniel Roth
Proceedings of 31th IEEE Virtual Reality Conference (VR ’24), Orlando, USA
Investigating Incoherent Depth Perception Features in Virtual Reality using Stereoscopic Impostor-Based Rendering
Kristoffer Waldow, Lukas Decker, Martin Misiak, Arnulph Fuhrmann, Daniel Roth, Marc Erich Latoschik
In:Proceedings of 31th IEEE Virtual Reality Conference (VR ’24), Orlando, USA
🏆Best Poster Award
Deep Neural Labeling: Hybrid Hand Pose Estimation Using Unlabeled Motion Capture Data With Color Gloves in Context of German Sign Language
Kristoffer Waldow, Arnulph Fuhrmann, Daniel Roth
6th IEEE International Conference on Artificial Intelligence & extended and Virtual Reality 2024 (AIxVR ’24)
An Evaluation of Dichoptic Tonemapping in Virtual Reality Experiences
Martin Mišiak, Tom Müller, Arnulph Fuhrmann and Marc Erich Latoschik
Virtuelle und Erweiterte Realität – 20. Workshop der GI-Fachgruppe VR/AR, 2023, Köln, Germany
Forschungsprojekt GTN – Games Technology Network
Das Vorhaben hat zum Ziel, ein Netzwerk von akademischen und Industrie-Partnern aufzubauen, das Forschung und Entwicklung in der Spieletechnologie in NRW befördert.
Investigating the Influence of Sound Source Visualization on the Ventriloquism Effect in an Auralized Virtual Reality Environment
Nigel Frangenberg, Kristoffer Waldow and Arnulph Fuhrmann
Proceedings of 28th IEEE Virtual Reality Conference (VR ’21), Lisbon, Portugal
AVASAG
Im Forschungsprojekt AVASAG wird ein Avatar-basierter Sprachassistent zur automatisierten Gebärdenübersetzung entwickelt.
Addressing Deaf or Hard-of-Hearing People in Avatar-Based Mixed Reality Collaboration Systems
We propose an easy to integrate Automatic Speech Recognition and textual visualization extension for an avatar-based MR remote collaboration system that visualizes speech via spatial floating speech bubbles. In a small pilot study, we achieved word accuracy of our extension of 97% by measuring the widely used word error rate.