ArticleFrontiers in robotics and AI2018
Tracking All Members of a Honey Bee Colony Over Their Lifetime Using Learned Models of Correspondence.
Article in Frontiers in robotics and AI, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- An open-source high-precision hive for long-term honeybee observation and research.Biology open · 2026Article
- SOPAR: Bee Localization and Tracking Using RF Sub-harmonic Oscillating Parametric Resonator in Hive Environments.Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies · 2026Article
- Neural Bases of Collective Social Behavior and Group Interactions across Species.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Review
- BeeCam-AprilTag: timing the flight duration of individual honey bees in remote field settings with AprilTag and Raspberry Pi.MethodsX · 2025Article
- A review of short-term weather impacts on honey production.International journal of biometeorology · 2025Review
- Automated entrance monitoring to investigate honey bee foraging trips using open-source wireless platform and fiducial tags.HardwareX · 2024Article
- How honeybees respond to heat stress from the individual to colony level.Journal of the Royal Society, Interface · 2023Article
- NAPS: Integrating pose estimation and tag-based tracking.Methods in ecology and evolution · 2023Article
- Machine learning reveals the waggle drift's role in the honey bee dance communication system.PNAS nexus · 2023Article
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- Integrating real-time data analysis into automatic tracking of social insects.Royal Society open science · 2021Article
- Markerless tracking of an entire honey bee colony.Nature communications · 2021Article
- Social networks predict the life and death of honey bees.Nature communications · 2021Article
- Tracking individual honeybees among wildflower clusters with computer vision-facilitated pollinator monitoring.PloS one · 2021Article
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- DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning.eLife · 2019Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computational approaches to the analysis of collective behavior in social insects increasingly rely on motion paths as an intermediate data layer from which one can infer individual behaviors or social interactions. Honey bees are a popular model for learning and memory. Previous experience has been shown to affect and modulate future social interactions. So far, no lifetime history observations have been reported for all bees of a colony. In a previous work we introduced a recording setup customized to track up to 4,000 marked bees over several weeks. Due to detection and decoding errors of the bee markers, linking the correct correspondences through time is non-trivial. In this contribution we present an in-depth description of the underlying multi-step algorithm which produces motion paths, and also improves the marker decoding accuracy significantly. The proposed solution employs two classifiers to predict the correspondence of two consecutive detections in the first step, and two tracklets in the second. We automatically tracked ~2,000 marked honey bees over 10 weeks with inexpensive recording hardware using markers without any error correction bits. We found that the proposed two-step tracking reduced incorrect ID decodings from initially ~13% to around 2% post-tracking. Alongside this paper, we publish the first trajectory dataset for all bees in a colony, extracted from ~3 million images covering 3 days. We invite researchers to join the collective scientific effort to investigate this intriguing animal system. All components of our system are open-source.
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