Survey of Fish Behavior Analysis by Computer Vision

@article{Niu2018SurveyOF,
  title={Survey of Fish Behavior Analysis by Computer Vision},
  author={Bingshan Niu and Guangyao Li and Fang Peng and Jing Wu and Long Zhang and Zhenbo Li},
  journal={Journal of Aquaculture Research and Development},
  year={2018},
  volume={9},
  pages={1-15}
}
Assessment of the behavior or physiology of cultured fish has always been difficult due to the sampling time, differences between experimental and aquaculture conditions, and methodological bias inherent. Recent developments in computer vision technology, however, have opened possibilities to better observe fish behavior. Such technology allows for non-destructive, rapid, economic, consistent, and objective inspection tools, while providing evaluation techniques based on image analysis and… 

Computer Vision Based Fish Tracking And Behaviour Detection System

  • S. SM. MUjjwal VermaR. Pai
  • Environmental Science
    2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER)
  • 2020
Computer vision-based technologies can be effectively adopted to enhance the performance and productivity of aquaculture industries. Application of these technologies can ease the life of fish

Automatic detection of fish and tracking of movement for ecology

TLDR
An integrated object detection and tracking pipeline is demonstrated a noninvasive and reliable approach to studying fish behavior by tracking their movement under field conditions and provides a means for future studies to scale‐up the analysis of movement across many visual monitoring systems.

A Review of Unmanned System Technologies with Its Application to Aquaculture Farm Monitoring and Management

TLDR
The capacity of unmanned vehicles as a communication gateway to facilitate offshore cages equipped with robust, low-cost sensors capable of underwater and in-air wireless connectivity is explored.

An assistive computer vision tool to automatically detect changes in fish behavior in response to ambient odor

TLDR
The overall objective of this work is to create a generalized tool to predict animal behaviors from videos using state-of-the-art deep learning models, with the dual goal of advancing understanding in biology and engineering a more robust and powerful artificial information processing system for biologists.

Intelligent fish farm—the future of aquaculture

TLDR
This paper reviews the application of fishery intelligent equipment, IoT, edge computing, 5G, and artificial intelligence algorithms in modern aquaculture, and analyzes the existing problems and future development prospects.

Behavioral analysis of rock bream Oplegnathus fasciatus reveals a strong attraction potential for sea urchin extracts

TLDR
The results suggest a higher potency of sea urchin extract as a rock bream fishing bait compared to the other materials that are used as commercial bait.

Monitoring methods of feeding behaviour to answer key questions in penaeid shrimp feeding

TLDR
Key questions that remain unanswered in relation to shrimp feeding behaviour under commercial aquaculture conditions are reviewed, and how they could be addressed using state-of-the-art applications based on three technologies commonly used in other areas of Aquaculture are considered.

Vision par ordinateur pour suivi automatique de civelles en bassin

TLDR
This article has developed an algorithm allowing to detect and track elvers in video sequences, using the background subtraction method and the labeling of connected components for extracting all information about elvers.

References

SHOWING 1-10 OF 181 REFERENCES

Near-infrared imaging to quantify the feeding behavior of fish in aquaculture

Fish telemetry in aquaculture: review and perspectives

TLDR
Knowing how key parameters are changing can allow faster adjustment of feeding times to activity rhythms, more objective identification of the preference/tolerance margins towards environmental variables and precise assessment of the impact of environmental or operational stressors on fish.

Measuring feeding activity of fish in RAS using computer vision

Sorting fish by computer vision

The Measurement of Fish Size by Machine Vision - A Review

TLDR
The methods reported can help researchers and farmers bring benefits for aquaculture and machine vision system brings high accuracy and high efficiency and is easier than manual work.

Observational methods used in marine spatial monitoring of fishes and associated habitats: a review

TLDR
The main finding from this review was that a combination of observational techniques, rather than a single method, was the most effective approach to marine spatial monitoring.

Predicting salmon biomass remotely using a digital stereo-imaging technique

Evaluation of Fish Behaviour and Aggregation by Underwater Videography in an Artificial Reef in Tioman Island , Malaysia

  • .. Kee
  • Environmental Science
  • 2010
The behaviour and aggregation of fish in an artificial reef area in Tioman Island, Malaysia, was observed using underwater videography under a combination of shooting conditions. The camera distance
...