SOCRATES: Introducing Depth in Visual Wildlife Monitoring Using Stereo Vision

The development and application of modern technology are an essential basis for the efficient monitoring of species in natural habitats to assess the change of ecosystems, species communities and populations, and in order to understand important drivers of change. For estimating wildlife abundance, camera trapping in combination with three-dimensional (3D) measurements of habitats is highly valuable. Additionally, 3D information improves the accuracy of wildlife detection using camera trapping. This study presents a novel approach to 3D camera trapping featuring highly optimized hardware and software. This approach employs stereo vision to infer the 3D information of natural habitats and is designated as StereO CameRA Trap for monitoring of biodivErSity (SOCRATES). A comprehensive evaluation of SOCRATES shows not only a 3.23% improvement in animal detection (bounding box mAP₇₅), but also its superior applicability for estimating animal abundance using camera trap distance sampling. The software and documentation of SOCRATES is openly provided.

Acknowledgments

This work is partially funded by the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung (BMBF, www.bmbf.de), Bonn, Gemany (AMMOD - Automated Multisensor Stations for Monitoring of BioDiversity: FKZ 01LC1903B). This funding is gratefully acknowledged.

We thank Vincent Mainzer and the team of the Tierpark Plittersdorf for their cooperation by hosting the camera trap hardware on site. We thank Frank Schindler for proofreading the manuscript.

We thank the creators of the following 3D parts which are used in the SOCRATES 3D model: Raspberry Pi HQ cameras (Inayat Rasool), Jetson Nano Devkit (Steven Minichiello), Infrared illuminator (Juan Andres Viera Medina), PIR sensor case (Mike Machado), LiPo battery (Pavel Stoudek).

Cite

In plaintext:

Haucke, T., Kühl, H. S., & Steinhage, V. (2022). SOCRATES: Introducing Depth in Visual Wildlife Monitoring Using Stereo Vision. Sensors, 22(23). https://doi.org/10.3390/s22239082

In BibTeX:

@article{haucke2022socrates,
author = {Haucke, Timm and Kühl, Hjalmar S. and Steinhage, Volker},
title = {SOCRATES: Introducing Depth in Visual Wildlife Monitoring Using Stereo Vision},
journal = {Sensors},
volume = {22},
year = {2022},
number = {23},
article-number = {9082},
url = {https://www.mdpi.com/1424-8220/22/23/9082},
issn = {1424-8220},
doi = {10.3390/s22239082}
}