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

Code: 9781801465137
Publication date: 27/06/2022
Extent: 30 pages

Contributions by: 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
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Table of contents
  • 1 Introduction
  • 2 Devices for data acquisition in computer visionbased systems
  • 3 Animal species and tasks analysed in computer vision systems for precision livestock farming
  • 4 Key elements of computer visionbased systems: initialisation
  • 5 Key elements of computer visionbased systems: tracking image segmentation
  • 6 Key elements of computer visionbased systems: tracking video object segmentation
  • 7 Key elements of computer visionbased systems: feature extraction
  • 8 Key elements of computer visionbased 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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