EE3P: Event-based Estimation of Periodic Phenomena Properties
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866916135474036736 |
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| author | Kolář, Jakub Špetlík, Radim Matas, Jiří |
| author_facet | Kolář, Jakub Špetlík, Radim Matas, Jiří |
| contents | We introduce a novel method for measuring properties of periodic phenomena with an event camera, a device asynchronously reporting brightness changes at independently operating pixels. The approach assumes that for fast periodic phenomena, in any spatial window where it occurs, a very similar set of events is generated at the time difference corresponding to the frequency of the motion. To estimate the frequency, we compute correlations of spatio-temporal windows in the event space. The period is calculated from the time differences between the peaks of the correlation responses. The method is contactless, eliminating the need for markers, and does not need distinguishable landmarks. We evaluate the proposed method on three instances of periodic phenomena: (i) light flashes, (ii) vibration, and (iii) rotational speed. In all experiments, our method achieves a relative error lower than 0.04%, which is within the error margin of ground truth measurements. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_14958 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | EE3P: Event-based Estimation of Periodic Phenomena Properties Kolář, Jakub Špetlík, Radim Matas, Jiří Computer Vision and Pattern Recognition I.4.8 We introduce a novel method for measuring properties of periodic phenomena with an event camera, a device asynchronously reporting brightness changes at independently operating pixels. The approach assumes that for fast periodic phenomena, in any spatial window where it occurs, a very similar set of events is generated at the time difference corresponding to the frequency of the motion. To estimate the frequency, we compute correlations of spatio-temporal windows in the event space. The period is calculated from the time differences between the peaks of the correlation responses. The method is contactless, eliminating the need for markers, and does not need distinguishable landmarks. We evaluate the proposed method on three instances of periodic phenomena: (i) light flashes, (ii) vibration, and (iii) rotational speed. In all experiments, our method achieves a relative error lower than 0.04%, which is within the error margin of ground truth measurements. |
| title | EE3P: Event-based Estimation of Periodic Phenomena Properties |
| topic | Computer Vision and Pattern Recognition I.4.8 |
| url | https://arxiv.org/abs/2402.14958 |