A brief review of the application of machine vision in livestock behaviour analysis

Matthew Tscharke, Thomas M. Banhazi


It is desirable to increase the frequency between livestock welfare assessments to enhance problem identification and consumer confidence in livestock welfare management. However, animal welfare is difficult to monitor in practice, due to the inefficiencies involved in manually documenting and determining, animal behaviour, social interaction and health condition of large numbers of animals. Furthermore, the effectiveness of a welfare assessment relies on the intuition of the observer which may vary considerably between assessors. Hence, this review investigates the application of machine vision systems to recognise and monitor the behaviour of animals in a quantitative manner. Behaviour-recognition concepts, techniques, and current behaviour monitoring systems are reviewed. Findings indicate that further research is required to develop systems that can monitor the behaviour and welfare of animals’ more efficiently and effectively in commercially realistic environments.

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DOI: 10.17700/jai.2016.7.1.279

Journal of Agricultural Informatics