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,...
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| Published in | Sensors (Basel, Switzerland) Vol. 22; no. 23; p. 9082 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
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23.11.2022
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| Abstract | 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. |
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| AbstractList | 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.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. 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 mAP[sub.75]), but also its superior applicability for estimating animal abundance using camera trap distance sampling. The software and documentation of SOCRATES is openly provided. 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 mAP 75 ), but also its superior applicability for estimating animal abundance using camera trap distance sampling. The software and documentation of SOCRATES is openly provided. 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. |
| Audience | Academic |
| Author | Haucke, Timm Steinhage, Volker Kühl, Hjalmar S. |
| AuthorAffiliation | 1 Institute of Computer Science IV, University of Bonn, Friedrich-Hirzebruch-Allee 8, 53115 Bonn, Germany 2 Senckenberg Museum for Natural History Görlitz, Senckenberg—Member of the Leibniz Association, Am Museum 1, 02826 Görlitz, Germany 4 German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstrasse 4, 04103 Leipzig, Germany 3 International Institute Zittau, Technische Universität Dresden, Markt 23, 02763 Zittau, Germany |
| AuthorAffiliation_xml | – name: 3 International Institute Zittau, Technische Universität Dresden, Markt 23, 02763 Zittau, Germany – name: 2 Senckenberg Museum for Natural History Görlitz, Senckenberg—Member of the Leibniz Association, Am Museum 1, 02826 Görlitz, Germany – name: 1 Institute of Computer Science IV, University of Bonn, Friedrich-Hirzebruch-Allee 8, 53115 Bonn, Germany – name: 4 German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstrasse 4, 04103 Leipzig, Germany |
| Author_xml | – sequence: 1 givenname: Timm orcidid: 0000-0003-1696-6937 surname: Haucke fullname: Haucke, Timm – sequence: 2 givenname: Hjalmar S. surname: Kühl fullname: Kühl, Hjalmar S. – sequence: 3 givenname: Volker orcidid: 0000-0002-3172-3645 surname: Steinhage fullname: Steinhage, Volker |
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| Keywords | animal abundance instance segmentation camera trapping animal density stereo vision |
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| SubjectTerms | 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 |
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| Title | SOCRATES: Introducing Depth in Visual Wildlife Monitoring Using Stereo Vision |
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