CamTraps 2024
Workshop on Camera Traps, AI, and Ecology 2024

Table of Contents

• Preface
  Summary: There were 12 papers submitted for peer-review to this workshop. Out of these, 10 papers were accepted for this volume, 5 as regular papers and 5 as short papers.

Session 1: Wildlife and Camera Trapping

• Improving Wildlife Management with AI: Species Detection and Classification from Camera Trap Data 1-14
  Sead Mustafic, Dominik Dachs, Rainer Prüller, Florian Schöggl, Roland Perko
• Utilizing Digital Elevation Models for Camera-Trap Distance Estimation (short paper) 15-21
  Leopold Böss, Stephanie Wohlfahrt, David C. Schedl
• Beyond Humanity: Leveraging Pre-trained Human Video Classification Models for Data-Efficient Multi-species Wildlife Animal Action Recognition (short paper) 22-29
  Wenxin Zhao
• How to Improve the Estimation of Red Deer (Cervus elaphus) Population Density in Serbia (short paper) 30-38
  Miroslav Urosevic, Jovan Mirceta, Bojan Tubic, Dejan Beukovic, Samantha Wisely

Session 2: Insect Monitoring

• High Resolution Environmental Monitoring of Pollinator Insects through Macro Camera Trapping and AI (short paper) 39-45
  Mohammad Sa'Doun, Daniel Dalton, Vanessa Berger, Gernot Paulus, Anders Karl-Heinrich, Ilja Svetnik, Johanna Schulz, Peter Unglaub
• TaxaNet: Harnessing a Hierarchical Loss Function for Insect Classification Using Deep Learning 46-56
  Chirag Padubidri, Heleen Visserman, Andreas Lanitis, Andreas Kamilaris

Session 3: Drones

• AUTH-Sheep: An Annotated Video Dataset for Detection and Tracking of Sheep in UAV Imagery 57-70
  Oliver Doll, Alexander Loos
• Object Geolocalization Using Consumer-Grade Devices: Algorithms and Applications 71-83
  Harald Lampesberger, Eckehard Hermann, Markus Zeilinger

Session 4: Digital-Nose

• Digi-Nose Part 1: Characterization of Volatile Organic Compounds (VOCs) Emitted by European Spruce Trees under Stress (short paper) 84-91
  Eva Olivia Huber, Sabrina Kröhnert, Georg Roman Schneider, Claudia Probst
• Digi-Nose Part 2: Enhancing Accuracy and Efficiency of a Digital Nose System with Sensor Technology for Early Detection of Changes in the Forest 92-104
  Leo Biljesko, Georg Roman Schneider, Claudia Probst