Automatic detection of locomotor play in young pigs : A proof of concept
Larsen, Mona Lilian Vestbjerg (Aarhus University. Department of Animal and Veterinary Sciences)
Wang, Meiqing (KU Leuven. Department of Biosystems)
Willems, Sam (KU Leuven. Department of Biosystems)
Liu, Dong (KU Leuven. Department of Biosystems)
Norton, Tomas (KU Leuven. Department of Biosystems)

Data:	2023
Resum:	Play behaviour is considered an indicator of animal welfare in young pigs. However, as play behaviour events are short-lasting and occur sporadically, continuous monitoring is necessary. This study presents a first attempt at automatic detection of locomotor play behaviour in young pigs from video by classifying locomotor play from other solitary behaviours including standing, walking, and running. Two methods were developed, compared, and sequentially combined: (1) a less computational heavy method utilising the Gaussian Mixture Model for quantification of movement combined with the calculation of contour features and standard machine learning classifiers (FEATURES); (2) a computational heavy method utilising a deep learning classifier taking both spatial and temporal features into account (DEEP). The DEEP classifier outperformed the FEATURES classifier and obtained values of internal validation recall, precision, and specificity of 94%, 88% and 96%, respectively. When combining the two classification methods, almost similar performance was retained, whilst 44% of the other behaviours were correctly classified without the need for deep learning methods. The combination thereby decreased the computational power needed to run the algorithm. Thus, locomotor play can be automatically detected in young pigs and the combination of a less computational heavy method with a deep learning method can reduce the computational requirements for the classification and detection of complex behaviours. Future work should focus on the segmentation of single pigs during high-speed activity in order to enable the play detection algorithm to work in real-life settings.
Ajuts:	European Commission 842555 European Commission 862919
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Llengua:	Anglès
Document:	Article ; recerca ; Versió acceptada per publicar
Publicat a:	Biosystems Engineering, Vol. 229 (May 2023) , p. 154-166, ISSN 1537-5129

DOI: 10.1016/j.biosystemseng.2023.03.006

Postprint 19 p, 920.9 KB

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