![]() ![]() Single camera capture, however, creates some limitations. These open source solutions are suitable tools to use when capturing with a single camera and with a known distance to the recorded object(s), with an exception for DLTdv as it performs triangulation when combined with calibration information provided by a different software. Software such as DLTdv ( Hedrick, 2008), Tracker (Open Source Physics) 1, ImageJ ( Rasband, 1997-2018), or Didge (Alistair Cullum, Creighton University) have usually been used to process the captured images. However, in most snake studies only one camera or a maximum of two are used to capture such rapid motion, with the one exception of a recent study where multiple cameras with only moderate temporal resolution, were used to investigate locomotor maneuvers ( Gart et al., 2019). Altshuler et al., 2005 Boeddeker et al., 2010 Geurten et al., 2010 Straw et al., 2011). High-speed video recording is a common tool to visualize and subsequently quantify fast behavioral performances such as in snakes ( Kardong and Bels, 1998 Young, 2010 Herrel et al., 2011 Penning et al., 2016 Ryerson and Tan, 2017), other fast moving animals ( Patek et al., 2004 Tobalske et al., 2007 Seid et al., 2008), or insect flight (e.g. Therefore, we conducted a case study investigating snake strike speed to showcase the use and integration of the software in an existing experimental setup. 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. 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. 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. 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. 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. Additionally, establishing custom-built software is often time consuming – especially for researchers without high-performance programming and computer vision expertise. 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. ![]() In many studies, solutions for video recording and subsequent tracking of animal behavior form a major bottleneck. 6Chair of Zoology, Technical University of Munich, Freising, GermanyĬurrent neuroethological experiments require sophisticated technologies to precisely quantify the behavior of animals.5Department Biology II, Ludwig-Maximilians-University Munich, Munich, Germany.4Institute of Zoology and Evolutionary Research, Friedrich-Schiller-University of Jena, Jena, Germany.3Department of Artificial Intelligence, Faculty of Informatics, Eötvös Lórand University, Budapest, Hungary.2argmax.ai, Volkswagen Group Machine Learning Research Lab, Munich, Germany.1Graduate School of Systemic Neurosciences (GSN-LMU), Ludwig-Maximilians-University Munich, Munich, Germany.Jensen 1,2* Patrick van der Smagt 1,2,3 Egon Heiss 4 Hans Straka 1,5 Tobias Kohl 6 ![]()
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