Detecting Animals in Infrared Images from Camera-Traps

P. Follmann, B. Radig

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Camera traps mounted on highway bridges capture millions of images that allow investigating animal populations and their behavior. As the manual analysis of such an amount of data is not feasible, automatic systems are of high interest. We present two different of such approaches, one for automatic outlier classification, and another for the automatic detection of different objects and species within these images. Utilizing modern deep learning algorithms, we can dramatically reduce the engineering effort compared to a classical hand-crafted approach. The results achieved within one day of work are very promising and are easily reproducible, even without specific computer vision knowledge.

Original languageEnglish
Pages (from-to)605-611
Number of pages7
JournalPattern Recognition and Image Analysis
Volume28
Issue number4
DOIs
StatePublished - 1 Oct 2018

Keywords

  • animal detection
  • outlier classification
  • wildlife monitoring

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