Monocular, Real-Time Surface Reconstruction using Dynamic Level of Detail

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.