Automatic Recognition of Aggressive Behavior in Pigs Using a Kinect Depth Sensor
AbstractAggression 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. View Full-Text
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Lee, J.; Jin, L.; Park, D.; Chung, Y. Automatic Recognition of Aggressive Behavior in Pigs Using a Kinect Depth Sensor. Sensors 2016, 16, 631.
Lee J, Jin L, Park D, Chung Y. Automatic Recognition of Aggressive Behavior in Pigs Using a Kinect Depth Sensor. Sensors. 2016; 16(5):631.Chicago/Turabian Style
Lee, Jonguk; Jin, Long; Park, Daihee; Chung, Yongwha. 2016. "Automatic Recognition of Aggressive Behavior in Pigs Using a Kinect Depth Sensor." Sensors 16, no. 5: 631.
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