Sea State Estimation from Uncalibrated, Monoscopic Video
Video of the ocean surface is used as a means for estimating the sea state. Time series of pixel intensity values are given as input to a method that uses the Kalman filter and the least squares approximate solution for estimating the uncalibrated video amplitude spectrum. A method is proposed for s...
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| Veröffentlicht in: | SN computer science 2021-07, Vol.2 (4), p.328, Article 328 |
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| creator | Loizou, Antonis Christmas, Jacqueline |
| description | Video of the ocean surface is used as a means for estimating the sea state. Time series of pixel intensity values are given as input to a method that uses the Kalman filter and the least squares approximate solution for estimating the uncalibrated video amplitude spectrum. A method is proposed for scaling this spectrum to metres with the use of an empirical model of the ocean. The significant wave height is estimated from the calibrated video amplitude spectrum. The results are tested against two sets of video data, and buoy measurements in both cases are solely used for indicating the true state. For significant wave height values between 0.5 and 3.6 m, the maximum observed value of root mean square error is 0.37 m and of mean absolute percentage error 16%. |
| doi_str_mv | 10.1007/s42979-021-00727-0 |
| format | Article |
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| subjects | Algorithms Amplitudes Approximation Bathymetry Cameras Computer Imaging Computer Science Computer Systems Organization and Communication Networks Data Structures and Information Theory Energy Fourier transforms Information Systems and Communication Service Kalman filters Maximum likelihood method Ocean surface Original Research Pattern Recognition and Graphics Sea states Software Engineering/Programming and Operating Systems State estimation Time series Video data Vision Wave height |
| title | Sea State Estimation from Uncalibrated, Monoscopic Video |
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