Team VERA

Computer Vision for Animal Conservation

The Video-based Re-Identification and Behaviour Analysis for Animals (VERA) project is an interdisciplinary collaboration led by the Machine Learning and Data Analytics Lab (MaD Lab). The VERA project forms a bridge between biological and ecological research and the machine learning field in order to develop a new generation of video-based algorithms for the tasks of re-identification of individual animals as well as detection of shown behaviour.

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General information

Re-Identification (Re-ID) Research

Get insights into the ongoing Re-ID research on animals, which involves using computer vision algorithms to identify individual animals in video footage based on their appearance and behavioural traits. This technology is a promising tool in wildlife conservation that allows researchers to study animal behaviour.

PolarBearVidID Dataset

Automatic behaviour analysis

Automatic behaviour analysis research on animals using re-ID methods involves using computer vision algorithms to identify and track individual animals in video footage and analyze their behaviour over time. This technology is decisive for understanding animal behaviour and can significantly improve captive animal welfare.

Stereotypy Detector

Team VERA

Matthias Zürl

Computer Scientist / Physicist
Researcher at Machine Learning and Data Analytics Lab
Friedrich-Alexander-Universität Erlangen-Nürnberg

Prof. Dr. Björn Eskofier

Computer Scientist
Head of Machine Learning and Data Analytics Lab
Friedrich-Alexander-Universität Erlangen-Nürnberg

Dr. Lorenzo von Fersen

Biologist
Curator for species conservation and research
Nuremberg Zoo

Dr. Ingrid Brehm

Biologist
Chair of Animal Physiology (Prof. Dr. Brandstätter)
Friedrich-Alexander-Universität Erlangen-Nürnberg

Dr. Ralph Simon

Biologist
Researcher at Behavioural Ecology and Conservation Lab
Nuremberg Zoo

Hana Tebelmann

Biologist
Applied Geography and Environmental Planning (Prof. Dr. Ingo Mose), Carl von Ossietzsky University Oldenburg