Implementation of machine vision for detecting behaviour of cattle and pigs

• Published in: Livestock science 2017-08, Vol.202, p.25-38
• Main Authors: Nasirahmadi, Abozar, Edwards, Sandra A., Sturm, Barbara
• Format: Article
• Language: English
• Subjects: Behaviour; Cattle; Machine vision; Pig; Precision livestock farming
• ISSN: 1871-1413; 1878-0490
• DOI: 10.1016/j.livsci.2017.05.014

Livestock production to provide food for a growing world population, with increasing demand for meat and milk products, has led to a rapid growth in the scale of cattle and pig enterprises globally. However, consumers and the wider society are also increasingly concerned about the welfare, health and living conditions of farm animals. Awareness of animal needs underpins new production standards for animal health and welfare. Pig and cattle behaviour can provide information about their barn environmental situation, food and water adequacy, health, welfare and production efficiency. Real-time scoring of cattle and pig behaviours is challenging, but the increasing availability and sophistication of technology makes automated monitoring of animal behaviour practicable. Machine vision techniques, as novel technologies, can provide an automated, non-contact, non-stress and cost-effective way to achieve animal behaviour monitoring requirements. This 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. The performance of developed systems is reviewed in terms of sensitivity, specificity, accuracy, error rate and precision. These technologies can support the farmer by monitoring normal behaviours and early detection of abnormal behaviours in large scale enterprises. •Application of 2D and 3D camera characterised in cattle and pigs monitoring.•Different image processing approaches for livestock evaluation have been surveyed.•Automatic monitoring of both individual and group animal behaviours reviewed.•Details of image processing methods were investigated in monitoring process.