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Machine vision techniques to monitor behaviour and health in precision livestock farming

Code: 9781801465137
C. Arcidiacono and S. M. C. Porto, University of Catania, Italy

Chapter synopsis: This chapter reviews advances in computer vision-based technologies for precision livestock farming. It also reviews how automation in image analysis can promote smart management of livestock to improve health and welfare. The chapter discusses the main devices for data acquisition in computer-vision based systems and the range of tasks computer vision (CV) techniques can perform. It reviews key steps such as initialisation, tracking, pose detection and recognition. The chapter includes illustrative case studies of precision livestock farming (PLF) applications based on existing CV techniques. The chapter concludes by reviewing recent advances in CV techniques based on artificial neural network (ANN) techniques, as well as future challenges.

DOI: 10.19103/AS.2021.0090.04
£25.00
Table of contents 1 Introduction 2 Devices for data acquisition in computer vision–based systems 3 Animal species and tasks analysed in computer vision systems for precision livestock farming 4 Key elements of computer vision–based systems: initialisation 5 Key elements of computer vision–based systems: tracking – image segmentation 6 Key elements of computer vision–based systems: tracking – video object segmentation 7 Key elements of computer vision–based systems: feature extraction 8 Key elements of computer vision–based systems: pose estimation and behaviour recognition 9 Case studies of precision livestock farming applications based on traditional computer vision techniques 10 Advances in computer vision techniques: deep learning 11 Case studies of precision livestock farming applications based on deep learning techniques 12 Conclusion 13 References

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