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Towards facial expression recognition for on-farm welfare assessment in pigs

Hansen, Mark F.; Baxter, Emma M.; Rutherford, Kenneth M. D.; Futro, Agnieszka; Smith, Melvyn L.; Smith, Lyndon N.

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Authors

Mark Hansen Mark.Hansen@uwe.ac.uk
Associate Professor in Knowledge Exchange & External Engagement

Emma M. Baxter

Kenneth M. D. Rutherford

Agnieszka Futro

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Melvyn Smith Melvyn.Smith@uwe.ac.uk
Research Centre Director Vision Lab/Prof

Lyndon Smith Lyndon.Smith@uwe.ac.uk
Professor in Computer Simulation and Machine



Abstract

Animal welfare is not only an ethically important consideration in good animal husbandry but can also have a significant effect on an animal’s productivity. The aim of this paper was to show that a reduction in animal welfare, in the form of increased stress, can be identified in pigs from frontal images of the animals. We trained a convolutional neural network (CNN) using a leave-one-out design and showed that it is able to discriminate between stressed and unstressed pigs with an accuracy of >90% in unseen animals. Grad-CAM was used to identify the animal regions used, and these supported those used in manual assessments such as the Pig Grimace Scale. This innovative work paves the way for further work examining both positive and negative welfare states with the aim of developing an automated system that can be used in precision livestock farming to improve animal welfare.

Citation

Hansen, M. F., Baxter, E. M., Rutherford, K. M. D., Futro, A., Smith, M. L., & Smith, L. N. (2021). Towards facial expression recognition for on-farm welfare assessment in pigs. Agriculture, 11(9), https://doi.org/10.3390/agriculture11090847

Journal Article Type Article
Acceptance Date Sep 1, 2021
Online Publication Date Sep 4, 2021
Publication Date Sep 4, 2021
Deposit Date Sep 9, 2021
Publicly Available Date Sep 15, 2021
Journal Agriculture
Print ISSN 2077-0472
Electronic ISSN 2077-0472
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 11
Issue 9
Article Number 847
DOI https://doi.org/10.3390/agriculture11090847
Keywords Plant Science; Agronomy and Crop Science; Food Science
Public URL https://uwe-repository.worktribe.com/output/7745804

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