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SnakeStrike: A Low-Cost Open-Source High-Speed Multi-Camera Motion Capture System

Current neuroethological experiments require sophisticated technologies to precisely quantify the behavior of animals. In many studies, solutions for video recording and subsequent tracking of animal behavior form a major bottleneck. Three-dimensional (3D) tracking systems have been available for a...

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Autores principales: Jensen, Grady W., van der Smagt, Patrick, Heiss, Egon, Straka, Hans, Kohl, Tobias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7416652/
https://www.ncbi.nlm.nih.gov/pubmed/32848652
http://dx.doi.org/10.3389/fnbeh.2020.00116
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author Jensen, Grady W.
van der Smagt, Patrick
Heiss, Egon
Straka, Hans
Kohl, Tobias
author_facet Jensen, Grady W.
van der Smagt, Patrick
Heiss, Egon
Straka, Hans
Kohl, Tobias
author_sort Jensen, Grady W.
collection PubMed
description Current neuroethological experiments require sophisticated technologies to precisely quantify the behavior of animals. In many studies, solutions for video recording and subsequent tracking of animal behavior form a major bottleneck. Three-dimensional (3D) tracking systems have been available for a few years but are usually very expensive and rarely include very high-speed cameras; access to these systems for research is limited. Additionally, establishing custom-built software is often time consuming – especially for researchers without high-performance programming and computer vision expertise. Here, we present an open-source software framework that allows researchers to utilize low-cost high-speed cameras in their research for a fraction of the cost of commercial systems. This software handles the recording of synchronized high-speed video from multiple cameras, the offline 3D reconstruction of that video, and a viewer for the triangulated data, all functions previously also available as separate applications. It supports researchers with a performance-optimized suite of functions that encompass the entirety of data collection and decreases processing time for high-speed 3D position tracking on a variety of animals, including snakes. Motion capture in snakes can be particularly demanding since a strike can be as short as 50 ms, literally twice as fast as the blink of an eye. This is too fast for faithful recording by most commercial tracking systems and therefore represents a challenging test to our software for quantification of animal behavior. Therefore, we conducted a case study investigating snake strike speed to showcase the use and integration of the software in an existing experimental setup.
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spelling pubmed-74166522020-08-25 SnakeStrike: A Low-Cost Open-Source High-Speed Multi-Camera Motion Capture System Jensen, Grady W. van der Smagt, Patrick Heiss, Egon Straka, Hans Kohl, Tobias Front Behav Neurosci Neuroscience Current neuroethological experiments require sophisticated technologies to precisely quantify the behavior of animals. In many studies, solutions for video recording and subsequent tracking of animal behavior form a major bottleneck. Three-dimensional (3D) tracking systems have been available for a few years but are usually very expensive and rarely include very high-speed cameras; access to these systems for research is limited. Additionally, establishing custom-built software is often time consuming – especially for researchers without high-performance programming and computer vision expertise. Here, we present an open-source software framework that allows researchers to utilize low-cost high-speed cameras in their research for a fraction of the cost of commercial systems. This software handles the recording of synchronized high-speed video from multiple cameras, the offline 3D reconstruction of that video, and a viewer for the triangulated data, all functions previously also available as separate applications. It supports researchers with a performance-optimized suite of functions that encompass the entirety of data collection and decreases processing time for high-speed 3D position tracking on a variety of animals, including snakes. Motion capture in snakes can be particularly demanding since a strike can be as short as 50 ms, literally twice as fast as the blink of an eye. This is too fast for faithful recording by most commercial tracking systems and therefore represents a challenging test to our software for quantification of animal behavior. Therefore, we conducted a case study investigating snake strike speed to showcase the use and integration of the software in an existing experimental setup. Frontiers Media S.A. 2020-08-03 /pmc/articles/PMC7416652/ /pubmed/32848652 http://dx.doi.org/10.3389/fnbeh.2020.00116 Text en Copyright © 2020 Jensen, van der Smagt, Heiss, Straka and Kohl. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Jensen, Grady W.
van der Smagt, Patrick
Heiss, Egon
Straka, Hans
Kohl, Tobias
SnakeStrike: A Low-Cost Open-Source High-Speed Multi-Camera Motion Capture System
title SnakeStrike: A Low-Cost Open-Source High-Speed Multi-Camera Motion Capture System
title_full SnakeStrike: A Low-Cost Open-Source High-Speed Multi-Camera Motion Capture System
title_fullStr SnakeStrike: A Low-Cost Open-Source High-Speed Multi-Camera Motion Capture System
title_full_unstemmed SnakeStrike: A Low-Cost Open-Source High-Speed Multi-Camera Motion Capture System
title_short SnakeStrike: A Low-Cost Open-Source High-Speed Multi-Camera Motion Capture System
title_sort snakestrike: a low-cost open-source high-speed multi-camera motion capture system
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7416652/
https://www.ncbi.nlm.nih.gov/pubmed/32848652
http://dx.doi.org/10.3389/fnbeh.2020.00116
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