Abstract
The automated video tracking of the activity/movement of an experimental organism is essential for reliable, repeatable quantitative analyses in behavioral ecology and also in other disciplines. There are only some open-access, open-source automated tracking software applications that can track unmarked organisms. Moreover, several of these software applications are substantially affected by brightness and differences in the lighting conditions of the video recording. Our Python-based software, called BugTracker, uses the latest innovations in computer vision technologies to solve these problems. By analyzing videos with considerably different lighting conditions with BugTracker and other available software, we demonstrate that our software could reliably track the studied organisms of any size and speed. Additionally, the results provide accurate measures of the organism’s movements. BugTracker is the most reliable currently available, easy-to-use, and automated tracking software compatible with the Windows, Linux, and MacOS operating systems.
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