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.

在移动的波浪表面上自动检测无源示踪剂在数学和工程中有许多应用。在海洋学中，在许多示例中，可以在波箱中使用向下看的常规光学相机来研究由波湍流引起的粒子弥散的机制。在这种情况下，我们提出了一种计算系统，可以在机械产生的具有不同光谱特征的水波的影响下，自动跟踪几个相同的无源漂浮物的轨迹。此类功能尚未公开可用，并且描述并评估了Python编程环境中的免费/开放源代码。该代码健壮且快速，能够在大约40秒内以30 fps的速度自动识别漂移器，而这些漂移器仍留在相机的视野中。