Sequential Fish Catch Counter Using Vision-based Fish Detection and Tracking

OCEANS 2022(2022)

引用 0|浏览1
暂无评分
摘要
An attempt has been made to develop a system for sequentially counting the number of fish caught using images taken on board. Fish catch counting for each local sea area contributes to fishery resource management and decision support for efficient operation. In this case, visual information is helpful for an intuitive explanation. The developed system consists of fish detection, fish tracking, and overdetected track deletion: to count fish robustly to its movement around on a deck, the fish detection stage attempts to absorb changes in the appearance of the fish, while the tracking stage dares not to use the appearance information to prevent the tracks from being unduly disconnected. Experimental comparisons using onboard video data of bullet tuna trolling demonstrated that the system could count fish with 89% precision and 87% recall.
更多
查看译文
关键词
Deep neural networks, object detection, object tracking, fish catch counting, bullet tuna trolling
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要