Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics
Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics
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Author / Creator
Weinreb, Caleb , Pearl, Jonah E. , Lin, Sherry , Osman, Mohammed Abdal Monium , Zhang, Libby , Annapragada, Sidharth , Conlin, Eli , Hoffmann, Red , Makowska, Sofia , Gillis, Winthrop F. , Jay, Maya , Ye, Shaokai , Mathis, Alexander , Mathis, Mackenzie W. , Pereira, Talmo , Linderman, Scott W. and Datta, Sandeep Robert
Publisher
New York: Nature Publishing Group US
Journal title
Language
English
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Publication information
Publisher
New York: Nature Publishing Group US
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Scope and Contents
Contents
Keypoint tracking algorithms can flexibly quantify animal movement from videos obtained in a wide variety of settings. However, it remains unclear how to parse continuous keypoint data into discrete actions. This challenge is particularly acute because keypoint data are susceptible to high-frequency jitter that clustering algorithms can mistake for...
Alternative Titles
Full title
Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics
Authors, Artists and Contributors
Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11245396
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11245396
Other Identifiers
ISSN
1548-7091,1548-7105
E-ISSN
1548-7105
DOI
10.1038/s41592-024-02318-2
