Automatic cattle location tracking using image processing

Research output: Contribution to conferencePaperpeer-review

14 Citations (Scopus)
227 Downloads (Pure)

Abstract

Behavioural scientists track animal behaviour patterns through the construction of ethograms which detail the activities of cattle over time. To achieve this, scientists currently view video footage from multiple cameras located in and around a pen, which houses the animals, to extract their location and determine their activity. This is a time consuming, laborious task, which could be automated. In this paper we extend the well-known Real-Time Compressive Tracking algorithm to automatically determine the location of dairy and beef cows from multiple video cameras in the pen. Several optimisations are introduced to improve algorithm accuracy. An automatic approach for updating the bounding box which discourages the algorithm from learning the background is presented. We also dynamically weight the location estimates from multiple cameras using boosting to avoid errors introduced by occlusion and by the tracked animal moving in and out of the field of view.
Original languageEnglish
Number of pages5
Publication statusPublished - Aug 2015
Event23rd European Signal Processing Conference, 2015 (EUSIPCO 2015) - Nice, France
Duration: 31 Aug 20154 Sept 2015

Conference

Conference23rd European Signal Processing Conference, 2015 (EUSIPCO 2015)
Abbreviated titleEUSIPCO 2015
Country/TerritoryFrance
CityNice
Period31/08/154/09/15

Keywords

  • location tracking
  • image processing
  • animal behaviour patterns
  • animal tracking

Fingerprint

Dive into the research topics of 'Automatic cattle location tracking using image processing'. Together they form a unique fingerprint.

Cite this