Automatic behaviour analysis system for honeybees using computer vision

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Automatic behaviour analysis system for honeybees using computer vision. / Tu, Gang Jun; Hansen, Mikkel Kragh; Kryger, Per; Ahrendt, Peter.

I: Computers and Electronics in Agriculture, Bind 122, Nr. March, 22.01.2016, s. 10-18.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

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Tu, Gang Jun o.a.. "Automatic behaviour analysis system for honeybees using computer vision". Computers and Electronics in Agriculture. 2016, 122(March). 10-18. https://doi.org/10.1016/j.compag.2016.01.011

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Author

Tu, Gang Jun ; Hansen, Mikkel Kragh ; Kryger, Per ; Ahrendt, Peter. / Automatic behaviour analysis system for honeybees using computer vision. I: Computers and Electronics in Agriculture. 2016 ; Bind 122, Nr. March. s. 10-18.

Bibtex

@article{d0109b69881d4eb0a82c33d33f7eef31,
title = "Automatic behaviour analysis system for honeybees using computer vision",
abstract = "We present a fully automatic online video system, which is able to detect the behaviour of honeybees at the beehive entrance. Our monitoring system focuses on observing the honeybees as naturally as possible (i.e. without disturbing the honeybees). It is based on the Raspberry Pi that is a low-cost embedded computer with very limited computational resources as compared to an ordinary PC. The system succeeds in counting honeybees, identifying their position and measuring their in-and-out activity. Our algorithm uses background subtraction method to segment the images. After the segmentation stage, the methods are primarily based on statistical analysis and inference. The regression statistics (i.e. R2) of the comparisons of system predictions and manual counts are 0.987 for counting honeybees, and 0.953 and 0.888 for measuring in-activity and out-activity, respectively. The experimental results demonstrate that this system can be used as a tool to detect the behaviour of honeybees and assess their state in the beehive entrance. Besides, the result of the computation time show that the Raspberry Pi is a viable solution in such real-time video processing system.",
keywords = "Video monitoring system, Raspberry Pi, Computer vision, Honeybees, Counting, In-and-out activity",
author = "Tu, {Gang Jun} and Hansen, {Mikkel Kragh} and Per Kryger and Peter Ahrendt",
year = "2016",
month = jan,
day = "22",
doi = "10.1016/j.compag.2016.01.011",
language = "English",
volume = "122",
pages = "10--18",
journal = "Computers and Electronics in Agriculture",
issn = "0168-1699",
publisher = "Elsevier BV",
number = "March",

}

RIS

TY - JOUR

T1 - Automatic behaviour analysis system for honeybees using computer vision

AU - Tu, Gang Jun

AU - Hansen, Mikkel Kragh

AU - Kryger, Per

AU - Ahrendt, Peter

PY - 2016/1/22

Y1 - 2016/1/22

N2 - We present a fully automatic online video system, which is able to detect the behaviour of honeybees at the beehive entrance. Our monitoring system focuses on observing the honeybees as naturally as possible (i.e. without disturbing the honeybees). It is based on the Raspberry Pi that is a low-cost embedded computer with very limited computational resources as compared to an ordinary PC. The system succeeds in counting honeybees, identifying their position and measuring their in-and-out activity. Our algorithm uses background subtraction method to segment the images. After the segmentation stage, the methods are primarily based on statistical analysis and inference. The regression statistics (i.e. R2) of the comparisons of system predictions and manual counts are 0.987 for counting honeybees, and 0.953 and 0.888 for measuring in-activity and out-activity, respectively. The experimental results demonstrate that this system can be used as a tool to detect the behaviour of honeybees and assess their state in the beehive entrance. Besides, the result of the computation time show that the Raspberry Pi is a viable solution in such real-time video processing system.

AB - We present a fully automatic online video system, which is able to detect the behaviour of honeybees at the beehive entrance. Our monitoring system focuses on observing the honeybees as naturally as possible (i.e. without disturbing the honeybees). It is based on the Raspberry Pi that is a low-cost embedded computer with very limited computational resources as compared to an ordinary PC. The system succeeds in counting honeybees, identifying their position and measuring their in-and-out activity. Our algorithm uses background subtraction method to segment the images. After the segmentation stage, the methods are primarily based on statistical analysis and inference. The regression statistics (i.e. R2) of the comparisons of system predictions and manual counts are 0.987 for counting honeybees, and 0.953 and 0.888 for measuring in-activity and out-activity, respectively. The experimental results demonstrate that this system can be used as a tool to detect the behaviour of honeybees and assess their state in the beehive entrance. Besides, the result of the computation time show that the Raspberry Pi is a viable solution in such real-time video processing system.

KW - Video monitoring system

KW - Raspberry Pi

KW - Computer vision

KW - Honeybees

KW - Counting

KW - In-and-out activity

U2 - 10.1016/j.compag.2016.01.011

DO - 10.1016/j.compag.2016.01.011

M3 - Journal article

VL - 122

SP - 10

EP - 18

JO - Computers and Electronics in Agriculture

JF - Computers and Electronics in Agriculture

SN - 0168-1699

IS - March

ER -