RT Journal Article
SR Electronic
T1 Automatic Analysis of Bees’ Waggle Dance
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.11.21.354019
DO 10.1101/2020.11.21.354019
A1 Jordan Reece
A1 Margaret Couvillon
A1 Christoph Grüter
A1 Francis Ratnieks
A1 Constantino Carlos Reyes-Aldasoro
YR 2020
UL http://biorxiv.org/content/early/2020/11/22/2020.11.21.354019.abstract
AB This work describe an algorithm for the automatic analysis of the waggle dance of honeybees. The algorithm analyses a video of a beehive with 13,624 frames, acquired at 25 frames/second. The algorithm employs the following traditional image processing steps: conversion to grayscale, low pass filtering, background subtraction, thresholding, tracking and clustering to detect run of bees that perform waggle dances. The algorithm detected 44,530 waggle events, i.e. one bee waggling in one time frame, which were then clustered into 511 waggle runs. Most of these were concentrated in one section of the hive. The accuracy of the tracking was 90% and a series of metrics like intra-dance variation in angle and duration were found to be consistent with literature. Whilst this algorithm was tested on a single video, the ideas and steps, which are simple as compared with Machine and Deep Learning techniques, should be attractive for researchers in this field who are not specialists in more complex techniques.Competing Interest StatementThe authors have declared no competing interest.