A visual tracking system for honeybee 3D flight trajectory reconstruction and analysis

  • Cong Sun

Student thesis: Phd


Although apiculture has been practised for thousands of years, many aspects of the honeybee, including the responses to the ambient environment through their central nervous system and their behaviours at an individual level, especially the flight behaviours, are yet to be understood thoroughly. Due to the dramatic decline in honeybee populations across the world, such studies have shown more significance. The development of instrumentation and software of an automated 3D insect detecting and tracking system is proposed. This inexpensive system comprises two orthogonally mounted video cameras with an observing volume of over 250 m3 and an offline analysis software system that outputs 3D space trajectories and inflight statistics of the target honeybees. The imaging devices record at 2.7K, 60 frames per second and require no human intervention once set up. The software module uses several forms of modern image processing techniques with GPU-enabled acceleration; it is able to minimise the effect of highly cluttered stationary background objects and moving artefacts whose characteristics are distinguishable from those of bees. The statistics of bees’ flight activity are presented and discussed. This system provides a streamlined and low-cost approach to the study of inflight behaviours of bees and other insects. It will find applications in the optimisation of pollination strategy, population dynamics and hive health, accurate knowledge of which is predicated upon a better understanding of the inflight behaviours of bees at the individual level.
Date of Award31 Aug 2021
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorPatrick Gaydecki (Supervisor) & Bruce Grieve (Supervisor)

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