A review on computer vision systems in monitoring of poultry: A welfare perspective

Monitoring of poultry welfare-related bio-processes and bio-responses is vital in welfare assessment and management of welfare-related factors. With the current development in information technologies, computer vision has become a promising tool in the real-time automation of poultry monitoring syst...

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Bibliographic Details
Published in:	Artificial intelligence in agriculture Vol. 4; pp. 184 - 208
Main Authors:	Okinda, Cedric, Nyalala, Innocent, Korohou, Tchalla, Okinda, Celestine, Wang, Jintao, Achieng, Tracy, Wamalwa, Patrick, Mang, Tai, Shen, Mingxia
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 2020 KeAi Communications Co., Ltd
Subjects:	Computer vision Deep learning Machine learning Monitoring Poultry Welfare Deep learning Computer vision Poultry Welfare Monitoring Machine learning
Online Access:	Get full text
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Summary:	Monitoring of poultry welfare-related bio-processes and bio-responses is vital in welfare assessment and management of welfare-related factors. With the current development in information technologies, computer vision has become a promising tool in the real-time automation of poultry monitoring systems due to its non-intrusive and non-invasive properties, and its ability to present a wide range of information. Hence, it can be applied to monitor several bio-processes and bio-responses. This review summarizes the current advances in poultry monitoring techniques based on computer vision systems, i.e., conventional machine learning-based and deep learning-based systems. A detailed presentation on the machine learning-based system was presented, i.e., pre-processing, segmentation, feature extraction, feature selection, and dimension reduction, and modeling. Similarly, deep learning approaches in poultry monitoring were also presented. Lastly, the challenges and possible solutions presented by researches in poultry monitoring, such as variable illumination conditions, occlusion problems, and lack of augmented and labeled poultry datasets, were discussed. •Recent advances and developments of poultry monitoring systems based on computer vision were reviewed.•Various poultry welfare-related bio-processes and bio-responses in poultry were presented.•Recently developed machine learning and deep learning-based approaches in poultry monitoring were covered.•Various challenges and possible solutions in poultry monitoring systems were discussed.
ISSN:	2589-7217 2589-7217
DOI:	10.1016/j.aiia.2020.09.002