ArticleeLife2021
TRex, a fast multi-animal tracking system with markerless identification, and 2D estimation of posture and visual fields.
Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 116 papers.
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Who cites it
116 citing papers in PubMed.
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- Using semi-folded arenas to observe spontaneous emergence of collective trails in whole colonies of termites.Movement ecology · 2026Article
- BullFish: Software for an automated stepwise analysis of positional and postural kinematics of zebrafish locomotion.iScience · 2026Article
- ManuTrace: An HTML-Based Interface for Manually Extracting Movement Trajectory Data From a Video.Ecology and evolution · 2026Article
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- Impact of hydrokinetic turbines on rainbow trout behaviour.Scientific reports · 2026Article
- Sociability is a Multidimensional Trait in Drosophila melanogaster.Behavior genetics · 2026Article
- Animal behavioral analysis and neural encoding with transformer-based self-supervised pretraining.ArXiv · 2026Article
- Ploidy and neuron size impact nervous system development and function in Xenopus.Cell reports · 2026Article
- YORU: Animal behavior detection with object-based approach for real-time closed-loop feedback.Science advances · 2026Article
- Evidence for natural selection shaping the evolution of collective behavior among globalbioRxiv : the preprint server for biology · 2026Article
- Joint modelling of brain and behaviour dynamics with artificial intelligence.Nature reviews. Neuroscience · 2026Review
- A Segment Anything Model-based tool for semi-automated behavioural analysis of Drosophila and other model organisms.Disease models & mechanisms · 2026Article
- Multimodal social context modulates larval behavior inScience advances · 2026Article
- The Lateral Line Facilitates Rapid Responses in Accelerating Fish Schools.Integrative and comparative biology · 2026Article
- Article
56 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Automated visual tracking of animals is rapidly becoming an indispensable tool for the study of behavior. It offers a quantitative methodology by which organisms' sensing and decision-making can be studied in a wide range of ecological contexts. Despite this, existing solutions tend to be challenging to deploy in practice, especially when considering long and/or high-resolution video-streams. Here, we present TRex, a fast and easy-to-use solution for tracking a large number of individuals simultaneously using background-subtraction with real-time (60 Hz) tracking performance for up to approximately 256 individuals and estimates 2D visual-fields, outlines, and head/rear of bilateral animals, both in open and closed-loop contexts. Additionally, TRex offers highly accurate, deep-learning-based visual identification of up to approximately 100 unmarked individuals, where it is between 2.5 and 46.7 times faster, and requires 2-10 times less memory, than comparable software (with relative performance increasing for more organisms/longer videos) and provides interactive data-exploration within an intuitive, platform-independent graphical user-interface.
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Registered trials
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