Automated posture recognition and behavior analysis in dairy cows using computer vision

Methodology: Combination of pose recognition and time series analysis

While pose recognition provides precise spatial information about the cow’s body posture at a given moment (e.g., lying, standing, feeding, drinking), time series analysis allows the evaluation of temporal behavioral patterns—such as high and low activity, frequency of position changes, restlessness, or deviations from the individual’s normal behavior.

Benefits: Early identification of behavioral anomalies

By combining both approaches, not only individual behaviors but also long-term dynamic behavior patterns can be identified—for example, early signs of impending calving, lameness, or stress. This enables timely, targeted intervention, which both enhances animal welfare and reduces farmers’ workload.

Technological approach: Robust, integrable camera systems

The system is based on non-invasive camera technology (RGB) and is designed to be robust, practical, and integrable into existing herd management systems (via licensing). Validation takes place under real barn conditions, with particular focus on scalability for farms of different sizes.

Outlook: Modular, economically viable analysis tool

In the long term, the aim is to create a modular tool that is economically viable and provides farmers with new, data-driven insights into animal behavior and animal health.