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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.17313 |
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| _version_ | 1866915230838161408 |
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| author | Maeda, Ryota Moon, Yunseong Baek, Seung-Hwan |
| author_facet | Maeda, Ryota Moon, Yunseong Baek, Seung-Hwan |
| contents | 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 capturing static scenes due to long acquisition times. Here, we introduce Event Ellipsometer, a method for acquiring a Mueller-matrix video for 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 video imaging at 30fps, extending ellipsometry to dynamic scenes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_17313 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Event Ellipsometer: Event-based Mueller-Matrix Video Imaging Maeda, Ryota Moon, Yunseong Baek, Seung-Hwan Computer Vision and Pattern Recognition 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 capturing static scenes due to long acquisition times. Here, we introduce Event Ellipsometer, a method for acquiring a Mueller-matrix video for 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 video imaging at 30fps, extending ellipsometry to dynamic scenes. |
| title | Event Ellipsometer: Event-based Mueller-Matrix Video Imaging |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2411.17313 |