Ahead of the upcoming Camera Trapping Sympoisum, organiser Arie Hammond has compiled a list of key resources for camera trapping, covering everything from reading lists for beginners to data sets, models and tools for advanced users. Want to add something to the list? Let us know here.
The Art and Science of Camera Trapping, Ryan Valdez
Camera trapping for conservation: A guide to best practices, Oliver Wearn & Paul Glover-Kapfer
Camera Trap Recommendations, eMammal
Stay up to date
Camera Trapping: Wildlife Management and Research, Paul Meek et al.
Camera Trapping for Wildlife Research (Data in the Wild), Francesco Rovero & Fridolin Zimmerman
We've collated these videos into a Camera Trapping playlist on the WILDLABS Youtube Channel.
Camera Setup 2016, Smithsonian eMammal
Camera Trapping 101 Installing your camera trap, Robert Vennell (Ecology Ngātahi)
How (Not) to Camera Trap in the Amazon Rainforest, Phil Torres
My Nature Watch - DIY wildlife camera, Bill Gaver and Mike Vanis
Software and Workflows
Timelapse, Saul Greenberg, University of Calgary
Camera Base, Mathias Tobler, San Diego Zoo Global
Agouti, Wageningen University & INBO
Wildlife Insights, Conservation International, NCMNS, WCS, & more
Zooniverse, University of Minnesota
MammalWeb, Durham University
Instant Wild, Zoological Society of London
ViXeN, Ramachandran & Devarajan
camtrapR, Niedballa et al.
5 Most common trail camera myths, Trail Cam Pro
HALT Camera Trap (for Herpetofauna and small mammals), Hobbs Ecology
NextGen Camera Trap Project, Conservation X Labs
Synthetic Examples Improve Generalization for Rare Classes, Beery et al,2019
Camera‐trapping version 3.0: current constraints and future priorities for development, Glover-Kapfer et al., 2019
An Animal Detection Pipeline for Identification, Parham et al, 2018
Responsible AI for Conservation, Wearn et al, 2019
A transient search using combined human and machine classifications, Wright et al, 2017
Models & Tools
Sensing Clues (Jan Kees)
Image Classifier, Willi et al.
AnDeNet (Animal Detection Network), Ersts & Horning
If this list isn't enough and you want more, check out Everything I know about Machine Learning and Camera Traps, compiled by Dan Morris.
About the Author
Arie Hammond is based at the San Diego Zoo Global Library, and is developing camera trap computer vision and digital curation practices with the Ecological Data Management research team at Rutgers. She also serves on the tech committee for Wildlife Insights, and as membership chair for SLA San Diego.
Header image: Jeremy Holden/FFI
Our camera trap community is where you can ask questions to discover best practice for using camera traps in your work.