Feature-Preserving Mesh Decimation for Normal Integration
This work addresses efficiency in 3D surface reconstruction for applications like photometric stereo, though it is incremental as it adapts existing mesh decimation techniques.
The paper tackles the computational burden of high-resolution normal integration by replacing dense pixel grids with sparse anisotropic triangle meshes, reducing runtimes from hours to minutes while preserving surface accuracy.
Normal integration reconstructs 3D surfaces from normal maps obtained e.g. by photometric stereo. These normal maps capture surface details down to the pixel level but require large computational resources for integration at high resolutions. In this work, we replace the dense pixel grid with a sparse anisotropic triangle mesh prior to normal integration. We adapt the triangle mesh to the local geometry in the case of complex surface structures and remove oversampling from flat featureless regions. For high-resolution images, the resulting compression reduces normal integration runtimes from hours to minutes while maintaining high surface accuracy. Our main contribution is the derivation of the well-known quadric error measure from mesh decimation for screen space applications and its combination with optimal Delaunay triangulation.