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Sensors 2016, 16(5), 631;

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

Department of Computer and Information Science, Korea University, Sejong Campus, Sejong City 30019, Korea
Ctrip Co., 99 Fu Quan Road, IT Security Center, Shanghai 200335, China
Authors to whom correspondence should be addressed.
Academic Editor: Simon X. Yang
Received: 3 March 2016 / Revised: 27 April 2016 / Accepted: 28 April 2016 / Published: 2 May 2016
(This article belongs to the Special Issue Sensors for Agriculture)
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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. View Full-Text
Keywords: pig aggression recognition; Kinect depth sensor; support vector machine pig aggression recognition; Kinect depth sensor; support vector machine

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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.

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