Accuracy Analysis of Photogrammetrically Derived Point Clouds for Partially Submerged Models
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There are many marine applications for 3D reconstruction ranging from the analysis of coastal erosion and bathymetric mapping using LiDAR to assisting in the structural health assessment of ships using photogrammetrically derived 3D models. As the quantity of data in all sectors of the global economy continue to grow, the historic methods of accomplishing activities such as structural inspections of ships must be succeeded by methods that cost less, save time, and provide for a safer work environment. The benefits from incorporating photogrammetrically derived 3D models can then clearly be seen when performing inspections on ships with the cost of Unmanned Aerial Systems (UAS), Unmanned Underwater Vehicles (UUV), and mounted camera systems replacing the cost of mobilizing equipment, reducing time to complete a task, and reducing the risks of in-person inspection. This study aimed to find out how accuracy was affected by merging two sets of photogrammetrically derived point cloud data that were not collected simultaneously, both above and below the water surface. Due to phenomena such as Snell’s law and barrel distortion, the image data and resulting 3D model can experience a decrease in accuracy to the real-world dimensions of a model in underwater sections compared to above water sections. This problem space has been harder to evaluate in prior work because of the typical subjects of partially submerged 3D models being large in scale, such as ships or caves, which results in non-exhaustive attempts to establish reference and control in complex physical environments To evaluate the impacts of these distortions, a new benchmark 3D model representative of a ship’s structural hull was designed, fabricated, and tested. This benchmark structure incorporated a uniform coordinate system based on target points along the surface of the hull shape, providing a basis for universal 3D reconstruction error. The impact of partial submersion on reconstruction accuracy was determined by comparing a fused model derived from a partially submerged benchmark model to a ground truth representation of the benchmark model that was unsubmerged. The results show that the absolute distance between the reference and fused model was less than 2 millimeters on average, but the maximum distances between the two models reached up to approximately 34 millimeters because of distortion caused by the water’s surface during 3D model generation. Future efforts should include the application of a benchmark uniform coordinate system on physical features of a greater scale. Additionally, the development of 3D model survey quality standards independent from a geospatial reference system is a critical future work opportunity. This would allow researchers to assess how the level of accuracy captured during one surveying effort compare to the level of accuracy in a subsequent survey.