ArticlePloS one2017
Automatic detection and decoding of honey bee waggle dances.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 48 citations in OpenAlex.
- An open-source high-precision hive for long-term honeybee observation and research.Biology open · 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
- Quantifying the honey bee dance floor: A data-driven method for defining and comparing waggle dance regions.PloS one · 2026Article
- Foraging distance distributions reveal how honeybee waggle dance recruitment varies with landscape.Communications biology · 2024Article
- Machine learning reveals the waggle drift's role in the honey bee dance communication system.PNAS nexus · 2023Article
- Responsiveness to inhibitory signals changes as a function of colony size in honeybees (Journal of the Royal Society, Interface · 2021Article
- Social networks predict the life and death of honey bees.Nature communications · 2021Article
- Behavior Individuality: A Focus onFrontiers in physiology · 2021Review
- Article
- Network-based diffusion analysis reveals context-specific dominance of dance communication in foraging honeybees.Nature communications · 2020Article
- Tracking All Members of a Honey Bee Colony Over Their Lifetime Using Learned Models of Correspondence.Frontiers in robotics and AI · 2018Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The waggle dance is one of the most popular examples of animal communication. Forager bees direct their nestmates to profitable resources via a complex motor display. Essentially, the dance encodes the polar coordinates to the resource in the field. Unemployed foragers follow the dancer's movements and then search for the advertised spots in the field. Throughout the last decades, biologists have employed different techniques to measure key characteristics of the waggle dance and decode the information it conveys. Early techniques involved the use of protractors and stopwatches to measure the dance orientation and duration directly from the observation hive. Recent approaches employ digital video recordings and manual measurements on screen. However, manual approaches are very time-consuming. Most studies, therefore, regard only small numbers of animals in short periods of time. We have developed a system capable of automatically detecting, decoding and mapping communication dances in real-time. In this paper, we describe our recording setup, the image processing steps performed for dance detection and decoding and an algorithm to map dances to the field. The proposed system performs with a detection accuracy of 90.07%. The decoded waggle orientation has an average error of -2.92° (± 7.37°), well within the range of human error. To evaluate and exemplify the system's performance, a group of bees was trained to an artificial feeder, and all dances in the colony were automatically detected, decoded and mapped. The system presented here is the first of this kind made publicly available, including source code and hardware specifications. We hope this will foster quantitative analyses of the honey bee waggle dance.
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