Abstract
We introduce a geometry-driven approach for real-time
3D reconstruction of deforming surfaces from a single
RGB-D stream without any templates or shape priors. To
this end, we tackle the problem of non-rigid registration by
level set evolution without explicit correspondence search.
Given a pair of signed distance fields (SDFs) representing
the shapes of interest, we estimate a dense deformation field
that aligns them. It is defined as a displacement vector field
of the same resolution as the SDFs and is determined iteratively via variational minimization. To ensure it generates
plausible shapes, we propose a novel regularizer that imposes local rigidity by requiring the deformation to be a
smooth and approximately Killing vector field, i.e. generating nearly isometric motions. Moreover, we enforce that the
level set property of unity gradient magnitude is preserved
over iterations. As a result, KillingFusion reliably reconstructs objects that are undergoing topological changes and
fast inter-frame motion. In addition to incrementally building a model from scratch, our system can also deform complete surfaces. We demonstrate these capabilities on several
public datasets and introduce our own sequences that permit both qualitative and quantitative comparison to related
approaches