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Fish tracking is a key technology for obtaining movement trajectories andidentifying abnormal behavior. However, it faces considerable challenges,including occlusion, multi-scale tracking, and fish deformation. Notably,extant reviews have focused more on behavioral analysis rather than providing acomprehensive overview of computer vision-based fish tracking approaches. Thispaper presents a comprehensive review of the advancements of fish trackingtechnologies over the past seven years (2017-2023). It explores diverse fishtracking techniques with an emphasis on fundamental localization and trackingmethods. Auxiliary plugins commonly integrated into fish tracking systems, suchas underwater image enhancement and re-identification, are also examined.Additionally, this paper summarizes open-source datasets, evaluation metrics,challenges, and applications in fish tracking research. Finally, acomprehensive discussion offers insights and future directions for vision-basedfish tracking techniques. We hope that our work could provide a partialreference in the development of fish tracking algorithms.

A Survey of Fish Tracking Techniques Based on Computer Vision