MS (Master of Science)
Date of Award
Committee Chair or Co-Chairs
Dr. Eileen Ernenwein
Dr. Blaine W. Schubert, Dr. Chris Widga
Natural caves represent one of the most difficult environments to map with modern 3D technologies. In this study I tested two relatively new methods for 3D mapping in Tipton-Haynes Cave near Johnson City, Tennessee: Structure from Motion Photogrammetry and Computer Vision using Tango, an RGB-D (Red Green Blue and Depth) technology. Many different aspects of these two methods were analyzed with respect to the needs of average cave explorers. Major considerations were cost, time, accuracy, durability, simplicity, lighting setup, and drift. The 3D maps were compared to a conventional cave map drafted with measurements from a modern digital survey instrument called the DistoX2, a clinometer, and a measuring tape. Both 3D mapping methods worked, but photogrammetry proved to be too time consuming and laborious for capturing more than a few meters of passage. RGB-D was faster, more accurate, and showed promise for the future of low-cost 3D cave mapping.
Thesis - unrestricted
Elmore, Clinton, "Comparing Structure from Motion Photogrammetry and Computer Vision for Low-Cost 3D Cave Mapping: Tipton-Haynes Cave, Tennessee" (2019). Electronic Theses and Dissertations. Paper 3608. https://dc.etsu.edu/etd/3608
Copyright by the authors.