CVPR 2025highlight0 citations

Event Ellipsometer: Event-based Mueller-Matrix Video Imaging

Ryota Maeda, Yunseong Moon, Seung-Hwan Baek

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.

BibTeX
@InProceedings{Maeda_2025_CVPR,
    author    = {Maeda, Ryota and Moon, Yunseong and Baek, Seung-Hwan},
    title     = {Event Ellipsometer: Event-based Mueller-Matrix Video Imaging},
    booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR)},
    month     = {June},
    year      = {2025},
    pages     = {21804-21813}
}
Event Ellipsometer: Event-based Mueller-Matrix Video Imaging · CVPR 2025