水下
计算机科学
计算机视觉
跟踪(教育)
目标检测
对象(语法)
人工智能
现成的
实时计算
遥感
模式识别(心理学)
地质学
海洋学
心理学
教育学
软件工程
作者
Xinliang Zhang,H. Zeng,Xiang Liu,Zhibin Yu,Haiyong Zheng,Bing Zheng
出处
期刊:IEEE Access
[Institute of Electrical and Electronics Engineers]
日期:2020-01-01
卷期号:8: 210041-210053
被引量:4
标识
DOI:10.1109/access.2020.3038643
摘要
Holothurian counting is a basic requirement in aquaculture. An in situ noncontact approach for holothurian counting is basically harmless, which makes such techniques an optimal choice for aquaculture monitoring. To develop an in situ noncontact counting system, there are two main challenges. In the underwater environment, the light is absorbed by the water, which distorts the underwater image color. Another challenge comes from the dynamic background, which makes it difficult to associate the ID to each holothurian. In this paper, we propose an effective usual framework for holothurian counting. The framework is composed of three modules: an underwater enhancement module, a multiple object detection module and a multiple object tracking module. To evaluate our system comprehensively, we collect and release the first underwater multiple object tracking dataset following the same format as MOT-16. The results show that our system can practically detect, track and count holothurians under different conditions.
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