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Estimating the swimming speed of salmon in aquaculture sea cages using computer vision
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Aqua2008_Pinkie...pdf | Download (35kB) Available under University of Tasmania Standard License. |
Abstract
In a commercial aquaculture farm, knowledge about fish behaviour can influence farm
management, fish growth and operating costs. In this presentation we describe research
towards the development of the first stage of a system that will track fish movement in a sea
cage and automatically analyse fish behaviour based on the movement. This first stage
involves the design and implementation of a tracking system that will calculate the average
speed and direction of fish in a sea cage. The system uses an underwater camera which
captures video to a digital recording device. Captured video is then analysed, using computer
vision software, to produce an average speed for every sampling period. The software can
track up to 8 fish at a time and uses the Kalman Filter technique for estimation of fish
position and the Global Nearest Neighbour algorithm for measurement-to-track association.
Item Type: | Conference or Workshop Item (Paper) |
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Authors/Creators: | Pinkiewicz, T and Purser, GJ and Williams, RN |
Item Statistics: | View statistics for this item |
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