SOCRATES: Introducing Depth in Visual Wildlife Monitoring Using Stereo Vision

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 23; p. 9082
• Main Authors: Haucke, Timm, Kühl, Hjalmar S., Steinhage, Volker
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 23.11.2022; MDPI
• Subjects: animal abundance; animal density; Animal populations; Animals; Animals, Wild; Automation; Biodiversity; Biological monitoring; Calibration; camera trapping; Cameras; Datasets; Deep learning; Ecosystem; instance segmentation; Sensors; Software; stereo vision; Technology application; Germany; animal abundance; instance segmentation; camera trapping; animal density; stereo vision
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22239082

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.