Computer Vision Models in Intelligent Aquaculture with Emphasis on Fish Detection and Behavior Analysis: A Review
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ORIGINAL PAPER
Computer Vision Models in Intelligent Aquaculture with Emphasis on Fish Detection and Behavior Analysis: A Review Ling Yang1,2,3 · Yeqi Liu1,2,3 · Huihui Yu5 · Xiaomin Fang1,2,4 · Lihua Song1,2,3 · Daoliang Li1,2,4 · Yingyi Chen1,2,3 Received: 3 January 2020 / Accepted: 24 August 2020 © CIMNE, Barcelona, Spain 2020
Abstract Intelligence technologies play an important role in increasing product quality and production efficiency in digital aquaculture. Automatic fish detection will contribute to achieving intelligent production and scientific management in precision farming. Due to the availability and ubiquity of modern information technology, such as the internet of things, big data, and camera devices, computer vision techniques, as an essential branch of artificial intelligence, have emerged as a powerful tool for achieving automatic fish detection. At present, it has been widely used in fish species identification, counting, and behavior analysis. Nevertheless, computer vision modeling used for fish detection is riddled with many challenges, such as varies in illumination, low contrast, high noise, fish deformation, frequent occlusion, and dynamic background. Hence, this paper provides a comprehensive review of the computer vision model for fish detection under unique application scenarios. Firstly, the image acquisition system based on 2D and 3D is discussed. Further, many fish detection techniques are categorized as appearance-based, motion-based, and deep learning. In addition, applications of fish detection and public open-source datasets are also presented in the literature. Finally, the prominent findings and the directions of future research are addressed toward the advancement in the aquaculture field throughout the discussion and conclusion section.
1 Introduction China is one of the most crucial aquaculture countries in the world, but there is still facing some problems with low digitalization, intelligence, and labor productivity. Smart * Yingyi Chen [email protected] 1
College of Information and Electrical Engineering, China Agricultural University, 17 Tsinghua East Road, Beijing 100083, People’s Republic of China
2
National Innovation Center for Digital Fishery, China Agricultural University, 17 Tsinghua East Road, Beijing 100083, People’s Republic of China
3
Beijing Engineering and Technology Research Centre for the Internet of Things in Agriculture, China Agricultural University, 17 Tsinghua East Road, Beijing 100083, People’s Republic of China
4
Precision Agricultural Technology Integration Research Base (Fishery), Ministry of Agriculture and Rural Affairs, China Agricultural University, 17 Tsinghua East Road, Beijing 100083, People’s Republic of China
5
School of Information Science and Technology, Beijing Forestry University, Beijing 100083, People’s Republic of China
aquaculture is also known as the third green revolution. It is a deep integration of modern information technology, such as the internet of things, big data, artificial intelligence,
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