Facial Expression Reconstruction with Photo-Reflective Sensors Embedded in a Head-Mounted Display

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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Reconstructing the 3D facial expressions of head-mounted display (HMD) wearers is essential for natural avatar communication in virtual reality (VR). Camera-based methods achieve high fidelity but involve heavy processing and privacy risks, whereas non-imaging sensors are lightweight and privacy-preserving but provide only sparse features. We propose a reconstruction system that learns high-dimensional 3D facial representations from camera images during training, but performs inference using only compact photo-reflective sensors embedded in the HMD. This design integrates the expressiveness of camera-based supervision with the efficiency and privacy of sensor-based operation. Experimental results show that our method accurately reconstructs 3D facial expressions from the sensor data, training with diverse wearing conditions is more effective than collecting more data under a single condition, and accuracy further improves with a dedicated mouth-shape predictor and lightweight personalization using small wearer-specific datasets.
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CCS Concepts: Human-centered computing → Virtual reality; Interaction devices

        
@inproceedings{
10.2312:egve.20251347
, booktitle = {
ICAT-EGVE 2025 - International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments
}, editor = {
Jorge, Joaquim A.
and
Sakata, Nobuchika
}, title = {{
Facial Expression Reconstruction with Photo-Reflective Sensors Embedded in a Head-Mounted Display
}}, author = {
Nakabayashi, Yuki
and
Nakamura, Fumihiko
and
Masai, Katsutoshi
and
Sugimoto, Maki
}, year = {
2025
}, publisher = {
The Eurographics Association
}, ISSN = {
1727-530X
}, ISBN = {
978-3-03868-278-3
}, DOI = {
10.2312/egve.20251347
} }
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