BioTracker: An Open-Source Computer Vision Framework for Visual Animal Tracking

Tim Landgraf, Benjamin Wild, Andreas Jörg, Tobias von Falkenhausen, Julian Tanke, David Dormagen, Jonas Piotrowski, Claudia Winklmayr, David Bierbach – 2018

The study of animal behavior increasingly relies on (semi-) automatic methods for the extraction of relevant behavioral features from video or picture data. To date, several specialized software products exist to detect and track animals' positions in simple (laboratory) environments. Tracking animals in their natural environments, however, often requires substantial customization of the image processing algorithms to the problem-specific image characteristics. Here we introduce BioTracker, an open-source computer vision framework, that provides programmers with core functionalities that are essential parts of a tracking software, such as video I/O, graphics overlays and mouse and keyboard interfaces. BioTracker additionally provides a number of different tracking algorithms suitable for a variety of image recording conditions. The main feature of BioTracker is however the straightforward implementation of new problem-specific tracking modules and vision algorithms that can build upon BioTracker's core functionalities. With this open-source framework the scientific community can accelerate their research and focus on the development of new vision algorithms.

Titel
BioTracker: An Open-Source Computer Vision Framework for Visual Animal Tracking
Verfasser
Tim Landgraf, Benjamin Wild, Andreas Jörg, Tobias von Falkenhausen, Julian Tanke, David Dormagen, Jonas Piotrowski, Claudia Winklmayr, David Bierbach
Datum
2018-03-21
Erschienen in
arXiv preprint arXiv: 1803.07985. 03/2018