@article{ref1,
title="Automatic recognition of aggressive behavior in pigs using a Kinect depth sensor",
journal="Sensors (Basel)",
year="2016",
author="Lee, Jonguk and Jin, Long and Park, Daihee and Chung, Yongwha",
volume="16",
number="5",
pages="s16050631-s16050631",
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.<p /> <p>Language: en</p>",
language="en",
issn="1424-8220",
doi="10.3390/s16050631",
url="http://dx.doi.org/10.3390/s16050631"
}