Abstract
We present a system that builds 3D models of non-rigidly
moving surfaces from scratch in real time using a single
RGB-D stream. Our solution is based on the variational
level set method, thus it copes with arbitrary geometry, including topological changes. It warps a given truncated
signed distance field (TSDF) to a target TSDF via gradient
flow. Unlike previous approaches that define the gradient
using an L2
inner product, our method relies on gradient
flow in Sobolev space. Its favourable regularity properties
allow for a more straightforward energy formulation that is
faster to compute and that achieves higher geometric detail,
mitigating the over-smoothing effects introduced by other
regularization schemes. In addition, the coarse-to-fine evolution behaviour of the flow is able to handle larger motions, making few frames sufficient for a high-fidelity reconstruction. Last but not least, our pipeline determines voxel
correspondences between partial shapes by matching signatures in a low-dimensional embedding of their Laplacian
eigenfunctions, and is thus able to reliably colour the output
model. A variety of quantitative and qualitative evaluations
demonstrate the advantages of our technique