Event Ellipsometer: Event-Based Mueller-Matrix Video Imaging
Abstract
Light-matter interactions modify both the intensity and polarization state of light. Changes in polarization, represented by a Mueller matrix, encode detailed scene information. Existing optical ellipsometers capture Mueller-matrix images; however, they are often limited to static scenes due to long acquisition times. Here, we introduce Event Ellipsometer, a method for acquiring Mueller-matrix images of dynamic scenes. Our imaging system employs fast-rotating quarter-wave plates (QWPs) in front of a light source and an event camera that asynchronously captures intensity changes induced by the rotating QWPs. We develop an ellipsometric-event image formation model, a calibration method, and an ellipsometric-event reconstruction method. We experimentally demonstrate that Event Ellipsometer enables Mueller-matrix imaging at 30fps, extending ellipsometry to dynamic scenes.
Cite
Text
Maeda et al. "Event Ellipsometer: Event-Based Mueller-Matrix Video Imaging." Conference on Computer Vision and Pattern Recognition, 2025. doi:10.1109/CVPR52734.2025.02031Markdown
[Maeda et al. "Event Ellipsometer: Event-Based Mueller-Matrix Video Imaging." Conference on Computer Vision and Pattern Recognition, 2025.](https://mlanthology.org/cvpr/2025/maeda2025cvpr-event/) doi:10.1109/CVPR52734.2025.02031BibTeX
@inproceedings{maeda2025cvpr-event,
title = {{Event Ellipsometer: Event-Based Mueller-Matrix Video Imaging}},
author = {Maeda, Ryota and Moon, Yunseong and Baek, Seung-Hwan},
booktitle = {Conference on Computer Vision and Pattern Recognition},
year = {2025},
pages = {21804-21813},
doi = {10.1109/CVPR52734.2025.02031},
url = {https://mlanthology.org/cvpr/2025/maeda2025cvpr-event/}
}