The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
idtracker.ai: tracking all individuals in small or large collectives of unmarked animals
Abstract
Understanding of animal collectives is limited by the ability to track each individual. We describe an algorithm and software that extract all trajectories from video, with high identification accuracy for collectives of up to 100 individuals. idtracker.ai uses two convolutional networks: one that detects when animals touch or cross and another for animal identification. The tool is trained with a protocol that adapts to video conditions and tracking difficulty. The idtracker.ai software tracks freely moving animals in large groups of up to 100 individuals. The tool is versatile and has been applied to groups of fruit flies, zebrafish, medaka, ants and mice.
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Cites
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Moen, E., Bannon, D., Kudo, T., Graf, W., Covert, M., & Van Valen, D. (2019) · Nature Methods · doi:10.1038/s41592-019-0403-1 · Cited by 1,225
SLEAP: A deep learning system for multi-animal pose tracking
Pereira, T. D., Tabris, N., Matsliah, A., Turner, D. M., Li, J., Ravindranath, S., Papadoyannis, E. S., Normand, E., Deutsch, D. S., Wang, Z. Y., et al. (2022) · Nature Methods · doi:10.1038/s41592-022-01426-1 · Cited by 886
Multi-animal pose estimation, identification and tracking with DeepLabCut
Lauer, J., Zhou, M., Ye, S., Menegas, W., Schneider, S., Nath, T., Rahman, M. M., Di Santo, V., Soberanes, D., Feng, G., et al. (2022) · Nature Methods · doi:10.1038/s41592-022-01443-0 · Cited by 647
DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning
Graving, J. M., Chae, D., Naik, H., Li, L., Koger, B., Costelloe, B. R., & Couzin, I. D. (2019) · eLife · doi:10.7554/elife.47994 · Cited by 547
Deep learning tools for the measurement of animal behavior in neuroscience
Mathis, M. W., & Mathis, A. (2020) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2019.10.008 · Cited by 450
Metadata
- Authors
- Romero-Ferrero, F., Bergomi, M. G., Hinz, R. C., Heras, F. J. H., & de Polavieja, G. G.
- Venue
- Nature Methods
- Published
- 2019-01-14
- Volume
- 16
- Issue
- 2
- Pages
- 179-182
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2908783938
- Cited by
- 406
- References
- 15
- FWCI
- 17.09
- Type
- journal article
- Language
- en
- Open access
- closed
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- Romero-Ferrero, F., Bergomi, M. G., Hinz, R. C., Heras, F. J. H., & de Polavieja, G. G. (2019). idtracker.ai: tracking all individuals in small or large collectives of unmarked animals. Nature Methods. https://doi.org/10.1038/s41592-018-0295-5
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