Tracking all members of a honey bee colony over their lifetime

by   Franziska Boenisch, et al.

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 tracking system customized to track up to 4000 bees over several weeks. In this contribution we present an in-depth description of the underlying multi-step algorithm which both produces the motion paths, and also improves the marker decoding accuracy significantly. We automatically tracked ∼2000 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 ∼ 4 million images. We invite researchers to join the collective scientific effort to investigate this intriguing animal system. All components of our system are open-source.


page 4

page 5

page 6

page 7


The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions

Multi-agent behavior modeling aims to understand the interactions that o...

Group Dynamics: Survey of Existing Multimodal Models and Considerations for Social Mediation

Social mediator robots facilitate human-human interactions by producing ...

Efficient Multiple Object Tracking Using Mutually Repulsive Active Membranes

Studies of social and group behavior in interacting organisms require hi...

Observing a group to infer individual characteristics

In the study of collective motion, it is common practice to collect move...

AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction

Anticipating human motion in crowded scenarios is essential for developi...

The Birth of Collective Memories: Analyzing Emerging Entities in Text Streams

We study how collective memories are formed online. We do so by tracking...

ViewpointS: towards a Collective Brain

Tracing knowledge acquisition and linking learning events to interaction...

Please sign up or login with your details

Forgot password? Click here to reset