An algorithm for tracking drifters dispersion induced by wave turbulence using optical cameras
The automatic detection of passive tracers on a moving wavy surface has numerous applications in mathematics and engineering. In oceanography, among many examples, down-looking conventional optical cameras can be employed in wave tanks to investigate the mechanisms of particle dispersion induced by...
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          | Published in | Computers & geosciences Vol. 148; p. 104654 | 
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| Main Authors | , , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
            Elsevier Ltd
    
        01.03.2021
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| Subjects | |
| Online Access | Get full text | 
| ISSN | 0098-3004 1873-7803  | 
| DOI | 10.1016/j.cageo.2020.104654 | 
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| Summary: | The automatic detection of passive tracers on a moving wavy surface has numerous applications in mathematics and engineering. In oceanography, among many examples, down-looking conventional optical cameras can be employed in wave tanks to investigate the mechanisms of particle dispersion induced by wave turbulence. In this context, we present a computational system to automatically track down the trajectories of several identical passive floaters under the influence of mechanically generated water waves with distinct spectral features. Such functionality is not yet publicly available and a free/open source code within the Python programming environment is described and evaluated. The code is robust and fast, able to automatically identify drifters at 30 fps during approximately 40 seconds, while they remained in the camera’s field of view. The algorithm is an efficient tool with many operational and scientific applications.
•A computational system to track down the trajectories of identical passive floaters.•The code is robust and fast, able to automatically identify drifters at 30 fps.•The algorithm has several applications, specially in wave tanks.•An efficient way to simultaneously track down several drifters on the water surface.•The results are robust, with high correlation and small errors. | 
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23  | 
| ISSN: | 0098-3004 1873-7803  | 
| DOI: | 10.1016/j.cageo.2020.104654 |