Name
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 animalsu0027 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 BioTrackeru0027s core functionalities. With this open-source framework the scientific community can accelerate their research and focus on the development of new vision algorithms. |
Year | Venue | Field |
|---|---|---|
2018 | arXiv: Computer Vision and Pattern Recognition | Graphics,Computer vision,Computer science,Animal behavior,Software,Artificial intelligence,Digital image processing,Overlay,Vision algorithms,Personalization |
DocType | Volume | Citations |
Journal | abs/1803.07985 | 0 |
PageRank | References | Authors |
0.34 | 5 | 10 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hauke Jürgen Mönck | 1 | 0 | 0.34 |
| Andreas Jörg | 2 | 0 | 0.34 |
| Tobias von Falkenhausen | 3 | 0 | 0.34 |
| Julian Tanke | 4 | 0 | 0.34 |
| Benjamin Wild | 5 | 18 | 3.43 |
| David Dormagen | 6 | 0 | 0.68 |
| Jonas Piotrowski | 7 | 0 | 0.34 |
| Claudia Winklmayr | 8 | 0 | 0.34 |
| David Bierbach | 9 | 9 | 2.05 |
| Tim Landgraf | 10 | 32 | 7.36 |