Documenting Outdoor Simulated Scenes with Photogrammetry

In both traditional and forensic archaeology, the thorough documentation of context is essential to a proper excavation or recovery, as the processing of archaeological sites and forensic scenes is an inherently destructive process. Over the past few decades, close-range photogrammetry (CRP) has become increasingly utilized by archaeologists to digitally record their excavations. However, CRP has not been employed regularly during outdoor forensic archaeological scene recoveries, and therefore protocols are not well defined for this context. One important consideration when employing CRP is the impact of natural lighting conditions. Light is an important variable when recording scenes using CRP because the quality of light can affect the visual quality of the model and imagery. In particular, shadows from the photographer's body, trees, and other structures are unavoidable when collecting images around the perimeter of scenes, a requirement of photogrammetry data collection. Therefore, the purpose of the present study was to determine whether implementing light correction tools would improve the three-dimensional model imagery. Two mock forensic scenes with different lighting conditions were photographed four times each in order to test the application of light correction tools, including a large tarp and artificial lights, for mitigating harsh lighting conditions. The results demonstrate that a tarp is a viable light correction tool that can improve the visual quality of the final models by eliminating lighting inconsistencies in both open and wooded environments. Based on these results, improved guidelines for the application of CRP to outdoor forensic archaeological scenes are presented

Archaeology · Computer vision · Context (archaeology · Documentation · Excavation · Geography · Photogrammetry · Process (computing · Quality (philosophy · 3D Surveying and Cultural Heritage · Computer Science · Conservation Techniques and Studies · Remote Sensing and LiDAR Applications · Artificial Intelligence