Implementation of machine vision for detecting behaviour of cattle and pigs
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TL;DR: In this article, a review describes the state of the art in 3D imaging systems (i.e., depth sensor and time of flight cameras) along with 2D cameras for effectively identifying livestock behaviours, and presents automated approaches for monitoring and investigation of cattle and pig feeding, drinking, lying, locomotion, aggressive and reproductive behaviours.
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About: This article is published in Livestock Science. The article was published on 01 Aug 2017. and is currently open access.
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Figures
Table 1- Validation criteria for machine vision techniques. 1132 
Fig. 1- The principles of 3D depth sensing. 1151 
Table 3- Summary of Automatic 2D and 3D image processing methods used for pig monitoring. 1147 
Table 2- Summary of automatic 2D and 3D image processing methods used for cattle monitoring. 1143
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Automated tracking to measure behavioural changes in pigs for health and welfare monitoring.
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Allan L. Schaefer,Nigel J. Cook,S. V. Tessaro,D. Deregt,G. Desroches,P. L. Dubeski,A. K. W. Tong,D. L. Godson +7 more
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Armağan Çolak,Bülent Polat,Zafer Okumuş,Muhammet Dursun Kaya,Latif Emrah Yanmaz,Armagan Hayirli +5 more
TL;DR: Infrared thermography is sensitive enough to perceive changes in SST in response to varying degrees of severity of the mammary gland infection as reflected by the CMT score, suggesting that as a noninvasive tool, IRT can be employed for screening dairy cows for mastitis.
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