TY  - INPR
A1  - Vishniakou, Ivan
A1  - Plöger, Paul G.
A1  - Seelig, Johannes D.
T1  - Virtual reality for animal navigation with camera-based optical flow tracking
N2  - Background: Virtual reality combined with spherical treadmills is used across species for studying neural circuits underlying navigation.
New Method: We developed an optical flow-based method for tracking treadmil ball motion in real-time using a single high-resolution camera.
Results: Tracking accuracy and timing were determined using calibration data. Ball tracking was performed at 500 Hz and integrated with an open source game engine for virtual reality projection. The projection was updated at 120 Hz with a latency with respect to ball motion of 30 ± 8 ms.
Comparison: with Existing Method(s) Optical flow based tracking of treadmill motion is typically achieved using optical mice. The camera-based optical flow tracking system developed here is based on off-the-shelf components and offers control over the image acquisition and processing parameters. This results in flexibility with respect to tracking conditions – such as ball surface texture, lighting conditions, or ball size – as well as camera alignment and calibration.
Conclusions: A fast system for rotational ball motion tracking suitable for virtual reality animal behavior across different scales was developed and characterized.
KW  - Virtual Reality
KW  - Navigation
KW  - Optical Flow
KW  - Spherical Treadmill
KW  - Ball Tracking
KW  - Drosophila
KW  - Real-Time Image Processing
Y1  - 2019
UR  - https://pub.h-brs.de/frontdoor/index/index/docId/4478
UR  - https://nbn-resolving.org/urn:nbn:de:hbz:1044-opus-44783
N1  - The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
N1  - Final version published in: J Neurosci Methods. 2019 Nov 1;327:108403. doi: 10.1016/j.jneumeth.2019.108403. Epub 2019 Aug 23.
PB  - bioRxiv
ER  -