Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Mar 21, 2026

Noninvasive, In-pen Approach Test for Laboratory-housed Pigs
06:30

Noninvasive, In-pen Approach Test for Laboratory-housed Pigs

Published on: June 5, 2019

9.0K

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

Jonguk Lee1, Long Jin2, Daihee Park3

  • 1Department of Computer and Information Science, Korea University, Sejong Campus, Sejong City 30019, Korea. eastwest9@korea.ac.kr.

Sensors (Basel, Switzerland)
|May 5, 2016
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Functional Electrical Stimulation Combined With Reactive Balance Training for Individuals With Incomplete Spinal Cord Injury: A Randomised Clinical Trial.

Neurorehabilitation and neural repair·2026
Same author

Comparison of methods for determining parameters related to ankle joint quasi-stiffness during quiet standing.

PloS one·2026
Same author

StaticPigDetv2: Performance Improvement of Unseen Pig Monitoring Environment Using Depth-Based Background and Facility Information.

Sensors (Basel, Switzerland)·2026
Same author

The Orthotic Effect of Functional Electrical Stimulation on Reactive Stepping for People With Incomplete Spinal Cord Injury.

Artificial organs·2025
Same author

Sustainable Self-Training Pig Detection System with Augmented Single Labeled Target Data for Solving Domain Shift Problem.

Sensors (Basel, Switzerland)·2025
Same author

Novel Method for Detecting Coughing Pigs with Audio-Visual Multimodality for Smart Agriculture Monitoring.

Sensors (Basel, Switzerland)·2024
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles
This summary is machine-generated.

Researchers developed a low-cost system using a Kinect depth sensor to automatically detect and classify aggressive behaviors in pigs. This non-invasive method achieves high accuracy, improving animal welfare and economic returns in pig farming.

Area of Science:

  • Animal Science
  • Agricultural Engineering
  • Computer Vision

Background:

  • Swine aggression negatively impacts farm economics and animal welfare.
  • Existing monitoring methods are often invasive or lack automation.
  • Objective assessment of pig behavior is crucial for welfare and productivity.

Purpose of the Study:

  • To develop a non-invasive, cost-effective, automated system for detecting and classifying aggressive behaviors in pigs.
  • To utilize Kinect depth sensor technology for real-time behavioral analysis in commercial pigsties.
  • To differentiate specific aggressive actions like head-knocking and chasing.

Main Methods:

  • Activity features were extracted from depth information captured by a Kinect sensor.
  • A hierarchical system of two binary-classifier support vector machines was employed.
Keywords:
Kinect depth sensorpig aggression recognitionsupport vector machine

More Related Videos

Automated Rat Single-Pellet Reaching with 3-Dimensional Reconstruction of Paw and Digit Trajectories
07:52

Automated Rat Single-Pellet Reaching with 3-Dimensional Reconstruction of Paw and Digit Trajectories

Published on: July 10, 2019

15.2K
A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents
06:25

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

Published on: May 16, 2025

1.6K

Related Experiment Videos

Last Updated: Mar 21, 2026

Noninvasive, In-pen Approach Test for Laboratory-housed Pigs
06:30

Noninvasive, In-pen Approach Test for Laboratory-housed Pigs

Published on: June 5, 2019

9.0K
Automated Rat Single-Pellet Reaching with 3-Dimensional Reconstruction of Paw and Digit Trajectories
07:52

Automated Rat Single-Pellet Reaching with 3-Dimensional Reconstruction of Paw and Digit Trajectories

Published on: July 10, 2019

15.2K
A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents
06:25

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

Published on: May 16, 2025

1.6K
  • The system was tested for its ability to detect and classify aggressive behaviors in a commercial pigpen setting.

    • Main Results:

    • The developed system demonstrated high effectiveness in detecting aggressive pig behaviors.
    • Detection accuracy exceeded 95.7%, and classification accuracy reached over 90.2%.
    • The method proved cost-effective due to the use of an inexpensive Kinect depth sensor.

    Conclusions:

    • The automated monitoring system offers a viable solution for identifying aggressive behaviors in pigs.
    • This technology can enhance animal welfare and economic outcomes in intensive pig farming.
    • The system can function as a standalone tool or supplement existing monitoring approaches.