photogrammetry-3d

To compute volume and surface area from a photogrammetry point cloud, you can use Open3D to clean statistical outliers and generate a Poisson mesh for exact geometric measurement. Density trimming removes artifacts to ensure accurate volume estimation.

Extracting cross-section profiles from 3D archaeological models involves processing reconstructed geometry to derive height and radius data. This supports comparative artifact analysis by mapping morphological variations across the 3D mesh.

Analyzing point cloud roughness and RGB color distribution is possible by computing surface normals for a roughness proxy and evaluating color values across distinct artifact zones. This enables detailed surface property visualization.

Open3D supports statistical outlier removal for photogrammetry point cloud cleaning to prepare geometry for reliable downstream measurements. Smoothing and filtering parameters can be configured for deterministic geometry processing.

The best way to remove Poisson mesh artifacts in 3D reconstruction is through density trimming. This technique cleans the generated triangle mesh, ensuring that subsequent surface area and volume calculations are not skewed by reconstruction noise.

To estimate volume when a 3D mesh is not watertight, the system can calculate an approximation using the available geometric data. While exact volume requires a watertight mesh, configurable reconstruction parameters help minimize approximation errors.