Geometry Processing and Analysis for Archaeology
Research Problem: Quickly identifying archaeological features in the form of curvelinear structures
Research Task: (1) Develop an efficient and accurate pipeline archaeology researchers, who are unfamiliar with coding, can easily use (2) Evaluate the accuracy of this tool using Ground-Penetrating-Radar (GPR) data, which exposes similar curvelinear structures underground
Actions: (3000+ lines of code)
- Created mesh from very-high-resolution LiDAR point cloud data from sites in Uzbekistan (Screened Poisson Reconstruction)
- Extracted curvelinear features from this mesh using the CrestCODE algorithm
- Extracted curvelinear features from GPR image using the Ridge-Detection algorithm
- Deformed the mesh as well as the curvelinear features to fit the distortion of the GPR image (due to reprojecting to a 2D plane) using the Smooth-Excess-Area algorithm
- Developed a metric to compare the curvelinear features from the deformed mesh and the GPR image
- Calculated summary statistics to identify the accuracy of our method
- Presented our results in the 2022 Undergraduate Research Symposium
- Our project was featured in the WashU's Technical Exchange Planning Meeting with the National Geospatial-Intelligence Agency (NGA)
- Discussed with archaeologists to confirm and update expectations for research outcome
- Produced well-documented, modularized code, which I circulated with new PhD students joining this project
- Reported findings in weekly project meetings
- Created an easy-to-use interface for all this automated pipeline
Results:
- Developed an efficient, user-friendly pipeline to automatically idenfity archaeological features in large scale
- Spearheaded and laid foundation for the collaboration between the two labs involved in this project
- Drafting: Reported our findings in a publication