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  Markerless tracking of user-defined anatomical features with deep learning

Mathis, M., Mathis, A., Mamidanna, P., Abe, T., Murthy, V., & Bethge, M. (2018). Markerless tracking of user-defined anatomical features with deep learning. Poster presented at 28th Annual Meeting of the Society for the Neural Control of Movement (NCM 2018), Santa Fe, NM, USA.

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Mathis, M, Author
Mathis, A, Author
Mamidanna, P, Author
Abe, T, Author
Murthy, V, Author
Bethge, M1, 2, Author              
Affiliations:
1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
2Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805              

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 Abstract: Quantifying behavior is crucial for many applications in neuroscience. Videography provides easy methods to observe animals, yet extracting particular aspects of a behavior can be highly time consuming. In motor control studies, humans or other animals are often marked with reflective markers to assist with computer-based tracking, yet markers are intrusive, especially for smaller animals, and the number and location of the markers must be determined a priori. Here we provide a highly efficient method of markerless tracking in mice based on transfer learning with very few training samples (~ 200 frames). We demonstrate the versatility of this framework by tracking various body parts of mice in different tasks: odor trail-tracking (by one or multiple mice simultaneously), and a skilled forelimb reach and pull task. For example, during the skilled reaching behavior, individual digit joints can be automatically tracked from the hand. Remarkably, even when a small number of frames are labeled, the algorithm achieves excellent tracking performance on test frames that is comparable to human accuracy.

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 Dates: 2018-05
 Publication Status: Published in print
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 Identifiers: BibTex Citekey: MathisMMAMB2018
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Title: 28th Annual Meeting of the Society for the Neural Control of Movement (NCM 2018)
Place of Event: Santa Fe, NM, USA
Start-/End Date: 2018-05-01 - 2018-05-04

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Title: 28th Annual Meeting of the Society for the Neural Control of Movement (NCM 2018)
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: 2-G-81 Start / End Page: 119 Identifier: -