Book

In recent years, the large-scale farming of commercial meat ducks has rapidly transitioned toward automation and digital intelligence. However, challenges such as occlusion, behavior ambiguity, and posture variability under intensive cage-rearing systems have hindered accurate perception and management of animal welfare. Machine Vision Empowered Intelligent Large-scale Waterfowl Farming provides a comprehensive exploration of vision-based intelligent technologies for behavior recognition and posture estimation in commercial meat ducks. By integrating deep learning, image processing, and sensor fusion, this book establishes an end-to-end framework that enables precise monitoring and intelligent decision-making in waterfowl production systems. The book systematically introduces the theoretical foundations of computer vision, the development of duck detection and segmentation algorithms, and the design of multi-keypoint posture estimation models. It also details the construction of real-time monitoring platforms and autonomous inspection robots for modern duck houses. Through innovative research on occlusion compensation, multi-scene adaptability, and fine-grained behavior understanding, the work bridges the gap between algorithmic innovation and engineering application in intelligent poultry farming. This volume serves as a valuable reference for researchers, engineers, and graduate students engaged in animal behavior analysis, precision livestock farming, and agricultural intelligent equipment design. Looking forward, it envisions a future of sustainable and welfare-oriented waterfowl farming, where machine vision and artificial intelligence jointly empower intelligent perception and management.