A computer vision system to analyse the swimming behaviour of farmed fish in commercial aquaculture facilities: A case study using cage-held Atlantic salmon

• Published in: Aquacultural Engineering
• Main Authors: Pinkiewicz, TH, Purser, GJ, Williams, RN
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier Sci Ltd 2011
• Subjects: Agricultural and Veterinary Sciences; Fisheries Sciences; Aquaculture; Atlantic salmon
• Online Access: https://doi.org/10.1016/j.aquaeng.2011.05.002; http://ecite.utas.edu.au/74412

Knowledge of fish behaviour plays an important role in aquaculture farm management. Video systems arethe most common and cost-effective way of observing behaviours in commercial aquaculture operations.However long term observation is not feasible due to a limited ability to analyse footage manually.This paper describes preliminary findings obtained via computer vision software that was developed toautomatically analyse fish movement and behaviours in aquaculture sea cages. Results show that thesystem is capable of detecting fish shapes in video recordings and from these shapes quantifying changesin swimming speed and direction continuously throughout the day. Also variations between days weredetected and these may have been associated with the daily shift in the tidal cycle. The system hasthe potential to act as an alarm to farm operators, informing them about unusual fish behaviours on acontinuous, real-time basis. It also has potential to assist in the evaluation of fish welfare.