IET Computer Vision (Mar 2018)

Tracking of group‐housed pigs using multi‐ellipsoid expectation maximisation

  • Mateusz Mittek,
  • Eric T. Psota,
  • Jay D. Carlson,
  • Lance C. Pérez,
  • Ty Schmidt,
  • Benny Mote

DOI
https://doi.org/10.1049/iet-cvi.2017.0085
Journal volume & issue
Vol. 12, no. 2
pp. 121 – 128

Abstract

Read online

Maintaining the health and well‐being of animals is critical to the efficiency and profitability of livestock operations. However, it can be difficult to monitor the health of animals in large group‐housed settings without the assistance of technology. This study presents a system that uses depth images to continuously track individual pigs in a group‐housed environment. It is an alternative to traditional manual observation used by both researchers and producers for the analysis of animal activities and behaviours. The tracking method used by the system exploits the consistent shape and fixed number of the targets in the environment by applying expectation maximisation as a policy for fitting an ellipsoid to each target. Results demonstrate that the system can maintain the correct positions and orientations of 15 group‐housed pigs for an average of 19.7 min between failure events.

Keywords