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DOI: 10.3791/58515-v
Jose A. Garcia*1,2, Valerio Sbragaglia*3,4, David Masip1, Jacopo Aguzzi2
1Universitat Oberta de Catalunya, 2Institute of Marine Sciences,Spanish National Research Council (CSIC), 3Institute for Environmental Protection and Research (ISPRA), 4Department of Biology and Ecology of Fishes,Leibniz-Institute of Freshwater Ecology and Inland Fisheries
Here we present a protocol to individually track animals over a long period of time. It uses computer vision methods to identify a set of manually constructed tags by using a group of lobsters as case study, simultaneously providing information on how to house, manipulate, and mark the lobsters.
This protocol allows automation of the tracking of multiple animals. Using a simple label to identify each animal an ID analysis tool to detect the tags. This protocol significantly reduces the number of hours needed to analyze the video recordings using leskey data.
to estimate more accurate completions from the experimental studies. Animals in other environments that can be tagged in similar fashion can be tracked with similar protocols providing application in chronobiology, ecology, viral research or neuroscience. We have provided the hardware design and open source programming language and provide a model we recommend users adopt in the protocols to learn Python programming language.
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