Journal ArticleDOI
idTracker: tracking individuals in a group by automatic identification of unmarked animals
Alfonso Pérez-Escudero,Julián Vicente-Page,Robert C. Hinz,Sara Arganda,Gonzalo G. de Polavieja +4 more
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TLDR
IdTracker as discussed by the authors extracts a characteristic fingerprint from each animal in a video recording of a group and then uses these fingerprints to identify every individual throughout the video, which prevents propagation of errors and the correct identities can be maintained indefinitely.Abstract:
Animals in groups touch each other, move in paths that cross, and interact in complex ways. Current video tracking methods sometimes switch identities of unmarked individuals during these interactions. These errors propagate and result in random assignments after a few minutes unless manually corrected. We present idTracker, a multitracking algorithm that extracts a characteristic fingerprint from each animal in a video recording of a group. It then uses these fingerprints to identify every individual throughout the video. Tracking by identification prevents propagation of errors, and the correct identities can be maintained indefinitely. idTracker distinguishes animals even when humans cannot, such as for size-matched siblings, and reidentifies animals after they temporarily disappear from view or across different videos. It is robust, easy to use and general. We tested it on fish (Danio rerio and Oryzias latipes), flies (Drosophila melanogaster), ants (Messor structor) and mice (Mus musculus).read more
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Journal ArticleDOI
DeepLabCut: markerless pose estimation of user-defined body parts with deep learning
Alexander Mathis,Pranav Mamidanna,Kevin M. Cury,Taiga Abe,Venkatesh N. Murthy,Mackenzie W. Mathis,Mackenzie W. Mathis,Matthias Bethge +7 more
TL;DR: Using a deep learning approach to track user-defined body parts during various behaviors across multiple species, the authors show that their toolbox, called DeepLabCut, can achieve human accuracy with only a few hundred frames of training data.
Journal ArticleDOI
Automated image-based tracking and its application in ecology
Anthony I. Dell,John A. Bender,Kristin Branson,Iain D. Couzin,Gonzalo G. de Polavieja,Lucas P. J. J. Noldus,Alfonso Pérez-Escudero,Pietro Perona,Andrew Straw,Martin Wikelski,Martin Wikelski,Ulrich Brose +11 more
TL;DR: Automated image-based tracking should continue to advance the field of ecology by enabling better understanding of the linkages between individual and higher-level ecological processes, via high-throughput quantitative analysis of complex ecological patterns and processes across scales, including analysis of environmental drivers.
Journal ArticleDOI
Fast animal pose estimation using deep neural networks.
Talmo D. Pereira,Diego E. Aldarondo,Diego E. Aldarondo,Lindsay Willmore,Mikhail Kislin,Samuel S.-H. Wang,Mala Murthy,Joshua W. Shaevitz +7 more
TL;DR: This work validated LEAP using videos of freely behaving fruit flies and tracked 32 distinct points to describe the pose of the head, body, wings and legs, with an error rate of<3% of body length and demonstrated LEAP’s applicability for unsupervised behavioral classification.
Journal ArticleDOI
Toward a Science of Computational Ethology
David J. Anderson,Pietro Perona +1 more
TL;DR: This work explores the opportunities and long-term directions of research in the new field of Computational Ethology, made possible by advances in technology, mathematics, and engineering that allow scientists to automate the measurement and the analysis of animal behavior.
Journal ArticleDOI
DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning
Jacob M. Graving,Daniel Chae,Hemal Naik,Liang Li,Liang Li,Benjamin Koger,Benjamin Koger,Blair R. Costelloe,Blair R. Costelloe,Iain D. Couzin,Iain D. Couzin +10 more
TL;DR: A new easy-to-use software toolkit, DeepPoseKit, is introduced that addresses animal pose estimation problems using an efficient multi-scale deep-learning model, called Stacked DenseNet, and a fast GPU-based peak-detection algorithm for estimating keypoint locations with subpixel precision.
References
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Journal ArticleDOI
Collective Motion
Tamás Vicsek,Anna Zafeiris +1 more
TL;DR: In this paper, the basic laws describing the essential aspects of collective motion are reviewed and a discussion of the various facets of this highly multidisciplinary field, including experiments, mathematical methods and models for simulations, are provided.
Journal ArticleDOI
Hierarchical group dynamics in pigeon flocks
TL;DR: The results suggest that hierarchical organization of group flight may be more efficient than an egalitarian one, at least for those flock sizes that permit regular pairwise interactions among group members, during which leader–follower relationships are consistently manifested.
Journal ArticleDOI
Scale-free correlations in starling flocks
Andrea Cavagna,Alessio Cimarelli,Irene Giardina,Giorgio Parisi,Raffaele Santagati,Fabio Stefanini,Massimiliano Viale +6 more
TL;DR: It is suggested that flocks behave as critical systems, poised to respond maximally to environmental perturbations, through scale-free behavioral correlations, which provide each animal with an effective perception range much larger than the direct interindividual interaction range, thus enhancing global response to perturbation.
Journal ArticleDOI
nacre encodes a zebrafish microphthalmia-related protein that regulates neural-crest-derived pigment cell fate.
TL;DR: It is demonstrated that melanophore development in fish and mammals shares a dependence on the nacre/Mitf transcription factor, but that proper development of the retinal pigment epithelium in the fish is not nacre-dependent, suggesting an evolutionary divergence in the function of this gene.
Journal ArticleDOI
High-throughput Ethomics in Large Groups of Drosophila
TL;DR: A camera-based method for automatically quantifying the individual and social behaviors of fruit flies, Drosophila melanogaster, interacting in a planar arena finds that behavioral differences between individuals were consistent over time and were sufficient to accurately predict gender and genotype.