Dataset Creation for the Artificial Intelligence-based Video Analysis of Yellow Hungarian Chicken Flocks - Rampasek, Éva; Hajdu, Csaba; Tüű Szabó, Boldizsár; Tempfli, Károly; Környei, László (GEORGIKON FOR AGRICULTURE, 2024)
A Precision Livestock Farming (PLF) system offers real-time insights into animal welfare and health, increasing production efficiency. Computer vision in the poultry industry enables automated monitoring of animals, providing a wealth of information without the need for human resources. The adoption of the “End the Cage Age” initiative by the European Commission will phase out caging of farm animals expectedly from 2027, impacting the laying hen sector, especially in Hungary where a significant portion of hens are currently raised in cage systems that are being replaced with cage-free systems requiring continuous monitoring of social behaviour. The initial step in implementing machine vision involves identifying hens and determining the number of individuals visible in images. The study involved automatic monitoring of various aspects such as behaviour, welfare, and health of Yellow Hungarian chickens at a breeding farm in Mosonmagyaróvár. Video recordings captured the activities of 49 hens in a controlled environment, focusing on detecting individual bird movements and predicting behaviours using advanced image processing techniques. The researchers utilized open bird datasets and annotation tools to create a specialized dataset for chicken behaviour analysis, showing promising results for future enhancements in detection and prediction capabilities.
Keywords: Hens; YOLO; precision livestock; deep learning; object tracking; object detection; artificial intelligence; computer vision