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bioRxiv · 10.1101/2022.03.29.486170

Validation of DeepLabCut as a tool for markerless 3D pose estimation

Kosourikhina, V.·Kavanagh, D.·Richardson, M. J.·Kaplan, D. M.
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Abstract

Deep learning-based approaches to markerless 3D pose estimation have taken neuroscience by storm. Yet many of these tools remain unvalidated. Here, we report on the validation of one increasingly popular tool (DeepLabCut) against simultaneous measurements obtained from a reference measurement system (Fastrak) with well-known performance characteristics. Our results confirm close (mm range) agreement between the two, indicating that deep learning-based approaches can be used by the research community with confidence.

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Kosourikhina, V., Kavanagh, D., Richardson, M. J., Kaplan, D. M.. 2022-03-29. Validation of DeepLabCut as a tool for markerless 3D pose estimation. https://doi.org/10.1101/2022.03.29.486170

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