@inproceedings{10.1007/978-3-032-06389-2_21,
title = {Human-Centric Emotion Recognition in VR for Humanities Research},
author = {Vasileios Sevetlidis and Vasileios Arampatzakis and George Pavlidis and Stella Sylaiou},
editor = {George Pavlidis and Stella Sylaiou},
url = {https://doi.org/10.1007/978-3-032-06389-2_21},
isbn = {978-3-032-06389-2},
year = {2025},
date = {2025-01-01},
urldate = {2025-01-01},
booktitle = {Transforming Heritage Research in a Transforming World: 5th CAA-GR Conference 2024},
pages = {219–227},
publisher = {Springer},
address = {Cham},
abstract = {Emotion recognition in Virtual Reality (VR) merges technology with humanities research, providing insights into human emotions in immersive environments. With VR expanding into education, healthcare, and social sciences, accurate emotion recognition is essential. This paper addresses the challenge of limited data by proposing a modified MixUp algorithm for VR emotion recognition. Our technique, which selectively combines data points within the same class, improves model generalization and accuracy. Testing on the VREED dataset demonstrates significant enhancements. This study reviews VR and emotion recognition technologies, details the class-intrinsic MixUp method, and discusses implications and future directions for humanities research using VR.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
