Image-based Tail Posture Monitoring of Pigs

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dc.contributor.authorWitte, Jan-Hendrik
dc.contributor.authorHeseker, Philipp
dc.contributor.authorProbst, Jeanette
dc.contributor.authorTraulsen, Imke
dc.contributor.authorKemper, Nicole
dc.contributor.authorGómez; Jorge Marx
dc.date.accessioned2023-12-27T04:57:40Z
dc.date.available2023-12-27T04:57:40Z
dc.date.issued2024-01-03
dc.identifier.doi10.24251/HICSS.2024.146
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.other9d018743-9294-4e93-bd30-100fabd2adb1
dc.identifier.urihttps://hdl.handle.net/10125/107327
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectDecision Systems for Smart Farming
dc.subjectpig
dc.subjectprecision livestock farming
dc.subjecttail posture detection
dc.subjectdeep learning
dc.subjectcomputer vision
dc.titleImage-based Tail Posture Monitoring of Pigs
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractTail 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.extent10
prism.startingpage7831

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