Fish tracking plays a vital role in understanding fish behavior and ecology. However, existing tracking methods face challenges in accuracy and robustness dues to morphological change of fish, occlusion and complex environment. This paper proposes FishMOT(Multiple Object Tracking for Fish), a novel fish tracking approach combining object detection and IoU matching, including basic module, interaction module and refind module. Wherein, a basic module performs target association based on IoU of detection boxes between successive frames to deal with morphological change of fish; an interaction module combines IoU of detection boxes and IoU of fish entity to handle occlusions; a refind module use spatio-temporal information uses spatio-temporal information to overcome the tracking failure resulting from the missed detection by the detector under complex environment. FishMOT reduces the computational complexity and memory consumption since it does not require complex feature extraction or identity assignment per fish, and does not need Kalman filter to predict the detection boxes of successive frame. Experimental results demonstrate FishMOT outperforms state-of-the-art multi-object trackers and specialized fish tracking tools in terms of MOTA, accuracy, computation time, memory consumption, etc.. Furthermore, the method exhibits excellent robustness and generalizability for varying environments and fish numbers. The simplified workflow and strong performance make FishMOT as a highly effective fish tracking approach. The source codes and pre-trained models are available at: https://github.com/gakkistar/FishMOT

翻译：鱼类追踪在理解鱼类行为与生态学中起着关键作用。然而，现有追踪方法因鱼类形态变化、遮挡及复杂环境等因素，在准确性与鲁棒性方面面临挑战。本文提出FishMOT（鱼类多目标追踪），一种结合目标检测与IoU匹配的新型鱼类追踪方法，包含基础模块、交互模块与重定位模块。其中，基础模块基于连续帧间检测框的IoU进行目标关联，以应对鱼类形态变化；交互模块结合检测框IoU与鱼体IoU处理遮挡问题；重定位模块利用时空信息克服复杂环境下因检测器漏检导致的追踪失败。FishMOT无需对每条鱼进行复杂特征提取或身份分配，亦无需卡尔曼滤波器预测后续帧检测框，从而降低了计算复杂度与内存消耗。实验结果表明，FishMOT在MOTA、准确率、计算时间、内存消耗等方面均优于当前最先进的多目标追踪器与专用鱼类追踪工具。此外，该方法在不同环境与鱼类数量下展现出优异的鲁棒性与泛化能力。简化的流程与强劲性能使FishMOT成为一种高效的鱼类追踪方法。源代码与预训练模型可通过以下链接获取：https://github.com/gakkistar/FishMOT