Automatic Recognition of Aggressive Behavior in Pigs Using a Kinect Depth Sensor.

Journal: Sensors (Basel, Switzerland)
Published Date:

Abstract

Aggression among pigs adversely affects economic returns and animal welfare in intensive pigsties. In this study, we developed a non-invasive, inexpensive, automatic monitoring prototype system that uses a Kinect depth sensor to recognize aggressive behavior in a commercial pigpen. The method begins by extracting activity features from the Kinect depth information obtained in a pigsty. The detection and classification module, which employs two binary-classifier support vector machines in a hierarchical manner, detects aggressive activity, and classifies it into aggressive sub-types such as head-to-head (or body) knocking and chasing. Our experimental results showed that this method is effective for detecting aggressive pig behaviors in terms of both cost-effectiveness (using a low-cost Kinect depth sensor) and accuracy (detection and classification accuracies over 95.7% and 90.2%, respectively), either as a standalone solution or to complement existing methods.

Authors

  • Jonguk Lee
    Department of Computer and Information Science, Korea University, Sejong Campus, Sejong City 30019, Korea. eastwest9@korea.ac.kr.
  • Long Jin
  • Daihee Park
    Department of Computer and Information Science, Korea University, Sejong Campus, Sejong City 30019, Korea. dhpark@korea.ac.kr.
  • Yongwha Chung
    Department of Computer and Information Science, Korea University, Sejong Campus, Sejong City 30019, Korea. ychungy@korea.ac.kr.