A Visual Tracking System for Honey Bee (Hymenoptera: Apidae) 3D Flight Trajectory Reconstruction and Analysis

Author:

Sun Cong1ORCID,Gaydecki Patrick1

Affiliation:

1. School of Electrical and Electronic Engineering, University of Manchester, Manchester M13 9PL, UK

Abstract

Abstract We describe the development, field testing, and results from an automated 3D insect flight detection and tracking system for honey bees (Apis mellifera L.) (Hymenoptera: Apidae) that is capable of providing remarkable insights into airborne behavior. It comprises two orthogonally mounted video cameras with an observing volume of over 200 m3 and an offline analysis software system that outputs 3D space trajectories and inflight statistics of the target honey bees. The imaging devices require no human intervention once set up and are waterproof, providing high resolution and framerate videos. The software module uses several forms of modern image processing techniques with GPU-enabled acceleration to remove both stationary and moving artifact while preserving flight track information. The analysis system has thus far provided information not only on flight statistics (such as speeds and accelerations), but also on subtleties associated with flight behavior by generating heat maps of density and classifying flight patterns according to patrol and foraging behavior. Although the results presented here focus on behavior in the locale of a beehive, the system could be adapted to study a wide range of airborne insect activity.

Publisher

Oxford University Press (OUP)

Subject

Insect Science,General Medicine

Reference32 articles.

1. The foraging behaviour of honey bees, Apis mellifera: a review;Abou-Shaara.;Vet. Med,2014

2. Automatically tracking and analyzing the behavior of live insect colonies,;Balch,2001

3. Fruit flies modulate passive wing pitching to generate in-flight turns;Bergou;Phys. Rev. Lett,2010

4. Fully-convolutional siamese networks for object tracking,;Bertinetto,2016

5. The conservation of bees: a global perspective;Brown;Apidologie,2009

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