  We introduce a novel method to obtain high-quality 3D reconstructions from
consumer RGB-D sensors. Our core idea is to simultaneously optimize for
geometry encoded in a signed distance field (SDF), textures from
automatically-selected keyframes, and their camera poses along with material
and scene lighting. To this end, we propose a joint surface reconstruction
approach that is based on Shape-from-Shading (SfS) techniques and utilizes the
estimation of spatially-varying spherical harmonics (SVSH) from subvolumes of
the reconstructed scene. Through extensive examples and evaluations, we
demonstrate that our method dramatically increases the level of detail in the
reconstructed scene geometry and contributes highly to consistent surface
texture recovery.
