English

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

Computer Vision and Pattern Recognition 2018-03-22 v1

Abstract

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.

Keywords

Cite

@article{arxiv.1803.07985,
  title  = {BioTracker: An Open-Source Computer Vision Framework for Visual Animal Tracking},
  author = {Hauke Jürgen Mönck and Andreas Jörg and Tobias von Falkenhausen and Julian Tanke and Benjamin Wild and David Dormagen and Jonas Piotrowski and Claudia Winklmayr and David Bierbach and Tim Landgraf},
  journal= {arXiv preprint arXiv:1803.07985},
  year   = {2018}
}

Comments

4 pages, 2 figures

R2 v1 2026-06-23T01:00:34.598Z