IET CV: Camera Traps, AI, and Ecology Call for Papers

Call for Papers - IET Computer Vision
Special Issue: Camera Traps, AI, and Ecology

Submission deadline: Friday, 15 December 2023

Website: https://ietresearch.onlinelibrary.wiley.com/hub/journal/17519640/homepage/call-for-papers/si-2023-000769

The development and integration of computer vision techniques into
research pipelines for biodiversity, species conservation, animal
husbandry, taxonomic research, and ecology has recently evolved from a
niche field into an ever more important and growing interdisciplinary
subject. Alongside drones, satellites, and manual photography, camera
traps form the most frequently employed, often most impactful, and
also cost-effective visual sensor class in large-scale use today. New
cross-disciplinary science directions such as imageomics and animal
biometrics are taking shape on the back of this increasing visual
sensor capacity bridging from visual measurement to biological
interpretation. Maybe most importantly though, ecological applications
of AI and specifically computer vision have started to make a positive
impact on the real-world monitoring of wildlife and related
conservation actions via tools for the detection, tracking, and
analysis of animals and their behaviours.

This special issue aims at providing a high-quality publication
platform in this interdisciplinary domain, in particular for novel
computer vision techniques, significant dataset contributions,
pioneering applicational work, and inspiring interdisciplinary
ventures that integrate vision engineering with ecological research.

Topics for this call for papers include but not restricted to:

    Camera trap datasets (images, image sequences, or videos) from
     wildlife camera traps, insect cameras, or other animal monitoring
     cameras (e.g., in a Zoo or other controlled environments)
    Animal detection (in images or videos)
    Identification of individuals and morphological traits (in images or videos)
    Species and fine-grained recognition approaches for animals (in images or videos)
    Animal pose estimation (in images or videos)
    Tracking of animal movement (in images or videos)
    Video recognition of animal behaviour
    Applying AI methods to camera trap data for answering ecological
     questions including new ecological questions or important open
     problems that can’t be solved with current AI approaches.

Guest Editors:

Tilo Burghardt
University of Bristol
United Kingdom

Majid Mirmehdi
University of Bristol
United Kingdom

Paul Bodesheim
University of Jena
Germany

Joachim Denzler
University of Jena
Germany

Dimitri Korsch
University of Jena
Germany

Otto Brookes
University of Bristol
United Kingdom

Marco Heurich
University of Freiburg
Germany

Hjalmar S. Kühl
Max Planck Institute
Germany
Dr.-Ing. Paul Bodesheim
Teamleiter / Team Leader: "Computer Vision and Machine Learning"

Lehrstuhl für Digitale Bildverarbeitung / Computer Vision Group
Fakultät für Mathematik und Informatik / Department of Mathematics and Computer Science
Friedrich-Schiller Universität Jena / Friedrich Schiller University Jena

Ernst-Abbe-Platz 2
07743 Jena, Germany

Telefon / Phone: +49 3641 9 46410
E-Mail: paul.bodesheim@uni-jena.de
Internet: https://www.inf-cv.uni-jena.de/bodesheim.html