Camera trapping technology and related advances: Into the new millennium

Paul D. Meek, Guy Ballard, Greg Falzon, Jaimen Williamson, Heath Milne, Robert Farrell, Joshua Stover, Atalya T. Mather-Zardain, James C. Bishop, Elrond Ka Wai Cheung, Christopher K. Lawson, Amos M. Munezero, Derek Schneider, Beau E. Johnston, Ehsan Kiani, Saleh Shahinfar, Edmund J. Sadgrove, Peter J.S. Fleming

Research output: Contribution to journalReview articlepeer-review

2 Citations (Scopus)

Abstract

Camera trapping has advanced significantly in Australia over the last two decades.These devices have become more versatile and the associated computer technology has also progressed dramatically since 2011. In the USA, the hunting industry drives most changes to camera traps; however the scientific fraternity has been instrumental in incorporating computational engineering, statistics and technology into camera trap use for wildlife research. New survey methods, analytical tools (including software for image processing and storage) and complex algorithms to analyse images have been developed. For example, pattern and texture analysis and species and individual facial recognition are now possible. In the next few decades, as technology evolves and ecological and computational sciences intertwine, new tools and devices will emerge into the market. Here we outline several projects that are underway to incorporate camera traps and associated technologies into existing and new tools for wildlife management. These also have significant implications for broader wildlife management and research.

Original languageEnglish
Pages (from-to)392-403
Number of pages12
JournalAustralian Zoologist
Volume40
Issue number3
DOIs
Publication statusPublished - 2020
Externally publishedYes

Keywords

  • Algorithm
  • Artificial intelligence
  • Automated alerts
  • Facial recognition
  • Image processing
  • Machine learning
  • Technology
  • Theft
  • Trail cameras

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