Poultry tracking system with camera using particle filters

Abstract

We developed a poultry tracking system for analyzing the behavior of poultry infected with avian influenza using a camera. The trackers employed in our system robustly track poultry that make contact and occlude each other in a narrow isolator during infection experiment using a particle filtering algorithm. This system has two kinds of trackers: poultry trackers and the exploring trackers. We used one poultry tracker for each target in the isolator. An exploring tracker searches and corrects a poultry tracker that failed. Further, complete overlap among trackers is avoided marking tracker positions on an image. We evaluated this system using 5 min video data on 10 healthy poultry. The results showed that our system can recognize and track poultry effectively; however, the durations for which poultry were tracked were not sufficient.