Automated tracking of aquatic crustaceans with potential application on the quantification of animals movement

Jesús D. Nuñez; Octavio Massone; José A. García

doi:10.25260/EA.23.33.1.0.1920

Authors

Jesús D. Nuñez Instituto de Investigaciones Marinas y Costeras (IIMyC), FCEyN, Universidad Nacional de Mar del Plata-CONICET. Mar del Plata, provincia de Buenos Aires, Argentina
Octavio Massone Instituto de Investigaciones Marinas y Costeras (IIMyC), FCEyN, Universidad Nacional de Mar del Plata-CONICET. Mar del Plata, provincia de Buenos Aires, Argentina
José A. García Universitat Oberta de Catalunya (UOC). Institute of Marine Sciences, Spanish National Research Council (ICM-CSIC)

DOI:

https://doi.org/10.25260/EA.23.33.1.0.1920

Keywords:

Python, OpenCV, object detection, video tracking, behavioural ecology

Abstract

Here, we present a set of algorithms using the Python programming language, that will allow using a routine for object detection and tracking in experimental videos. We developed a script, under the fundamentals of background subtraction and image thresholding (using the OpenCV package), that makes it possible to track a wide spectrum of animals under different conditions. We have validated this script through testing on semi-terrestrial and aquatic crustacean species and under different experimental scenarios (laboratory and field sampling and using video created under nocturnal and diurnal conditions). The open-source nature of the script allows for flexibility and scalability, so it can be easily customized and is thus transferable to other species/experiments in the context of behavioral ecology. The tracking script is easy customizable and free alternative to commercial video tracking systems and therefore, applicable to a wide variety of both educational and research programs.

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