تقرير
A Survey of Fish Tracking Techniques Based on Computer Vision
العنوان: | A Survey of Fish Tracking Techniques Based on Computer Vision |
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المؤلفون: | Li, Weiran, Li, Zhenbo, Li, Fei, Yuan, Meng, Cen, Chaojun, Qi, Yanyu, Guo, Qiannan, Li, You |
سنة النشر: | 2021 |
المجموعة: | Computer Science |
مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition |
الوصف: | Fish tracking is a key technology for obtaining movement trajectories and identifying 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 a comprehensive overview of computer vision-based fish tracking approaches. This paper presents a comprehensive review of the advancements of fish tracking technologies over the past seven years (2017-2023). It explores diverse fish tracking techniques with an emphasis on fundamental localization and tracking methods. Auxiliary plugins commonly integrated into fish tracking systems, such as 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, a comprehensive discussion offers insights and future directions for vision-based fish tracking techniques. We hope that our work could provide a partial reference in the development of fish tracking algorithms. Comment: Substantial revisions, deletions and supplements have been made in this version to enhance readability and sharpen the logical flow |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2110.02551 |
رقم الأكسشن: | edsarx.2110.02551 |
قاعدة البيانات: | arXiv |
الوصف غير متاح. |