Automatic Recognition of Aggressive Behavior in Pigs Using a Kinect Depth Sensor
- Authors
- Lee, Jonguk; Jin, Long; Park, Daihee; Chung, Yongwha
- Issue Date
- 5월-2016
- Publisher
- MDPI
- Keywords
- pig aggression recognition; Kinect depth sensor; support vector machine
- Citation
- SENSORS, v.16, no.5
- Indexed
- SCIE
SCOPUS
- Journal Title
- SENSORS
- Volume
- 16
- Number
- 5
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/88779
- DOI
- 10.3390/s16050631
- ISSN
- 1424-8220
- 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.
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- Appears in
Collections - College of Science and Technology > Department of Computer Convergence Software > 1. Journal Articles
- Graduate School > Department of Computer and Information Science > 1. Journal Articles
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