Accurately tracking a group of small biological organisms using algorithms to obtain their movement trajectories is essential to biomedical and pharmaceutical research. However, object mis-detection, segmentation errors and overlapped individual trajectories are particularly common issues that restrict the development of automatic multiple small organism tracking research. Extending on previous work, this paper presents an accurate and generalised Multiple Small Biological Organism Tracking System (MSBOTS), whose general feasibility is tested on three types of organisms. Evaluated on zebrafish, Artemia and Daphnia video datasets with a wide variety of imaging conditions, the proposed system exhibited decreased overall Multiple Object Tracking Precision (MOTP) errors of up to 77.59%. Moreover, MSBOTS obtained more reliable tracking trajectories with a decreased standard deviation of up to 47.68 pixels compared with the state-of-the-art idTracker system. This paper also presents a behaviour analysis module to study the locomotive characteristics of individual organisms from the obtained tracking trajectories. The developed MSBOTS with the locomotive analysis module and the tested video datasets are made freely available online for public research use.

中文翻译：

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MSBOTS：针对非理想检测和分割条件的多小生物有机体跟踪系统

使用算法准确跟踪一组小型生物有机体以获得它们的运动轨迹对于生物医学和药物研究至关重要。然而，对象误检测、分割错误和重叠的个体轨迹是特别常见的问题，限制了自动多小生物跟踪研究的发展。在先前工作的基础上，本文提出了一种准确且通用的多小生物体跟踪系统 (MSBOTS)，其一般可行性在三种生物体上进行了测试。在具有各种成像条件的斑马鱼、卤虫和水蚤视频数据集上进行评估，所提出的系统表现出降低的整体多目标跟踪精度 (MOTP) 误差高达 77.59%。而且，与最先进的 idTracker 系统相比，MSBOTS 获得了更可靠的跟踪轨迹，标准偏差降低了高达 47.68 像素。本文还提出了一个行为分析模块，从获得的跟踪轨迹研究个体生物的运动特征。已开发的带有机车分析模块的 MSBOTS 和经过测试的视频数据集可免费在线获取以供公众研究使用。