Image-based Tail Posture Monitoring of Pigs

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dc.contributor.author Witte, Jan-Hendrik
dc.contributor.author Heseker, Philipp
dc.contributor.author Probst, Jeanette
dc.contributor.author Traulsen, Imke
dc.contributor.author Kemper, Nicole
dc.contributor.author Gómez; Jorge Marx
dc.date.accessioned 2023-12-27T04:57:40Z
dc.date.available 2023-12-27T04:57:40Z
dc.date.issued 2024-01-03
dc.identifier.isbn 978-0-9981331-7-1
dc.identifier.other 9d018743-9294-4e93-bd30-100fabd2adb1
dc.identifier.uri https://hdl.handle.net/10125/107327
dc.language.iso eng
dc.relation.ispartof Proceedings of the 57th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Decision Systems for Smart Farming
dc.subject pig
dc.subject precision livestock farming
dc.subject tail posture detection
dc.subject deep learning
dc.subject computer vision
dc.title Image-based Tail Posture Monitoring of Pigs
dc.type Conference Paper
dc.type.dcmi Text
dcterms.abstract Tail biting presents a significant challenge in conventional pig farming, impacting animal welfare and farmers' economic viability. This paper introduces a novel approach for image-based tail posture monitoring, a potential early indicator of tail biting outbreaks. Our two-step tail posture detection approach, consisting of an initial pig detection and a subsequent tail posture detection step, shows significant improvements compared to previous methods. To mitigate ambiguity, our pipeline incorporates an EfficientNetV2 image classification model, filtering out lying pigs in the tail posture monitoring process. When applied to video sequences containing tail biting incidents, our method effectively captures the shift in tail posture from predominantly upright to hanging preceding outbreaks. Our findings offer a promising foundation for an early warning system to aid undocked pig husbandry, improve animal welfare, and provide targeted insights for farmers. The proposed approach demonstrates the potential for real-world applications, fostering proactive interventions to mitigate tail biting.
dcterms.extent 10
prism.startingpage 7831
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