Biderman, Dan, Whiteway, Matthew R, Hurwitz, Cole, Greenspan, Nicholas, Lee, Robert S, Vishnubhotla, Ankit, Warren, Richard, Pedraja, Federico, Noone, Dillon, Schartner, Michael M, Huntenburg, Julia M, Khanal, Anup, Meijer, Guido T, Noel, Jean-Paul, Pan-Vazquez, Alejandro, Socha, Karolina Z, Urai, Anne E, International Brain Laboratory, Cunningham, John P, Sawtell, Nathaniel B, Paninski, Liam (July 2024) Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling and cloud-native open-source tools. Nature Methods, 21 (7). pp. 1316-1328. ISSN 1548-7091
Abstract
Contemporary pose estimation methods enable precise measurements of behavior via supervised deep learning with hand-labeled video frames. Although effective in many cases, the supervised approach requires extensive labeling and often produces outputs that are unreliable for downstream analyses. Here, we introduce 'Lightning Pose', an efficient pose estimation package with three algorithmic contributions. First, in addition to training on a few labeled video frames, we use many unlabeled videos and penalize the network whenever its predictions violate motion continuity, multiple-view geometry and posture plausibility (semi-supervised learning). Second, we introduce a network architecture that resolves occlusions by predicting pose on any given frame using surrounding unlabeled frames. Third, we refine the pose predictions post hoc by combining ensembling and Kalman smoothing. Together, these components render pose trajectories more accurate and scientifically usable. We released a cloud application that allows users to label data, train networks and process new videos directly from the browser.
| Item Type: | Paper |
|---|---|
| Subjects: | bioinformatics bioinformatics > computational biology > algorithms organism description > animal behavior bioinformatics > computational biology bioinformatics > computational biology > algorithms > machine learning |
| CSHL Authors: | |
| Communities: | CSHL labs > Churchland lab CSHL labs > Engel lab CSHL labs > Zador lab |
| SWORD Depositor: | CSHL Elements |
| Depositing User: | CSHL Elements |
| Date: | July 2024 |
| Date Deposited: | 30 Sep 2024 15:17 |
| Last Modified: | 01 Oct 2024 17:33 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/41688 |
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