We present a scalable, real-time capable method for robust
surface reconstruction that explicitly handles multiple
scales. As a monocular camera browses a scene, our
algorithm processes images as they arrive and incrementally
builds a detailed surface model. While most of the
existing reconstruction approaches rely on volumetric or
point-cloud representations of the environment, we perform
depth-map and colour fusion directly into a multi-resolution
triangular mesh that can be adaptively tessellated using
the concept of Dynamic Level of Detail. Our method relies
on least-squares optimisation, which enables a probabilistically
sound and principled formulation of the fusion
algorithm. We demonstrate that our method is capable of
obtaining high quality, close-up reconstruction, as well as
capturing overall scene geometry, while being memory and
computationally efficient.