A Machine Vision-Based Method for Monitoring Scene-Interactive Behaviors of Dairy Calf

摘要

Requirements for dairy products are increasing gradually in emerging economic bodies such as China, so it is critical to monitor and maintain the health and welfare of the increasing population of dairy cattle, especially dairy calves (over 20% mortality). In this study, a new method was built by combining background-subtraction and inter-frame difference methods to monitor the behaviors of dairy calf. By using the new model and motion characteristics of the calf in different areas of the enclosure, the scene-interactive behaviors of entering or leaving the resting area, turning around, and stationary (no movement) were identified automatically with a 93–97% success rate. This newly developed method provides a basis for inventing evaluation tools to monitor calves’ health and welfare on dairy farms.