Automatic Recognition of Aggressive Behavior in Pigs Using a Kinect Depth Sensor
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Jonguk | - |
dc.contributor.author | Jin, Long | - |
dc.contributor.author | Park, Daihee | - |
dc.contributor.author | Chung, Yongwha | - |
dc.date.accessioned | 2021-09-04T00:09:55Z | - |
dc.date.available | 2021-09-04T00:09:55Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2016-05 | - |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/88779 | - |
dc.description.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. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | MDPI | - |
dc.subject | CLASSIFICATION | - |
dc.subject | SOWS | - |
dc.title | Automatic Recognition of Aggressive Behavior in Pigs Using a Kinect Depth Sensor | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Park, Daihee | - |
dc.contributor.affiliatedAuthor | Chung, Yongwha | - |
dc.identifier.doi | 10.3390/s16050631 | - |
dc.identifier.scopusid | 2-s2.0-84976317531 | - |
dc.identifier.wosid | 000375153900038 | - |
dc.identifier.bibliographicCitation | SENSORS, v.16, no.5 | - |
dc.relation.isPartOf | SENSORS | - |
dc.citation.title | SENSORS | - |
dc.citation.volume | 16 | - |
dc.citation.number | 5 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Chemistry | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Instruments & Instrumentation | - |
dc.relation.journalWebOfScienceCategory | Chemistry, Analytical | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Instruments & Instrumentation | - |
dc.subject.keywordPlus | CLASSIFICATION | - |
dc.subject.keywordPlus | SOWS | - |
dc.subject.keywordAuthor | pig aggression recognition | - |
dc.subject.keywordAuthor | Kinect depth sensor | - |
dc.subject.keywordAuthor | support vector machine | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.