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Improvement of Honey Bee Tracking on 2D Video with Hough Transform and Kalman Filter

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Abstract

This paper introduces a novel approach to improve bee tracking. For this research, 50 Hz 2D videos have been recorded. The first part of the model tracks bees using a method combining colour thresholding and foreground detection, and then produces the bees’ shapes as blobs on a binary image. These blobs are analysed to estimate the positions and directions of motion of the bees. However, when bees cross over one another in the image, they are hard to track. This paper tackles this problem by using the standard Hough transform applied to bee research. Then a Kalman filter is used to track the bees using their estimated position information. Because of the 50 Hz frame rate, the trajectories of the bee movements are too variable to track reliably. The Kalman filter is modified to fit this situation. Multiple bees are being tracked, so the Hungarian assignment algorithm is used to assign predictions and measurements to individual bees. The experiment shows the bees are reliably tracked in the close view 50 Hz 2D video.

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Acknowledgements

The paper is supported by Darren Bainbridge, who provided access to beehives.

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Authors and Affiliations

  1. School of Engineering, Computer & Mathematical Sciences, Auckland University of Technology, 34 St Paul Street, City Campus, Auckland, New Zealand

    Cheng Yang & John Collins

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  1. Cheng Yang
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  2. John Collins
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Correspondence to Cheng Yang.

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Yang, C., Collins, J. Improvement of Honey Bee Tracking on 2D Video with Hough Transform and Kalman Filter. J Sign Process Syst 90, 1639–1650 (2018). https://doi.org/10.1007/s11265-017-1307-x

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  • DOI: https://doi.org/10.1007/s11265-017-1307-x

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