Sensing Surface Patches in Volume Rendering for Inferring Signed Distance Functions

Jing Hua

Abstract:

It is vital to recover 3D geometry from multi-view RGB im-
ages in many 3D computer vision tasks. The latest methods
infer the geometry represented as a signed distance field by
minimizing the rendering error on the field through volume
rendering. However, it is still challenging to explicitly im-
pose constraints on surfaces for inferring more geometry de-
tails due to the limited ability of sensing surfaces in volume
rendering. To resolve this problem, we introduce a method to
infer signed distance functions (SDFs) with a better sense of
surfaces through volume rendering. Using the gradients and
signed distances, we establish a small surface patch centered
at the estimated intersection along a ray by pulling points
randomly sampled nearby. Hence, we are able to explicitly
impose surface constraints on the sensed surface patch, such
as multi-view photo consistency and supervision from depth
or normal priors, through volume rendering. We evaluate our
method by numerical and visual comparisons on scene bench-
marks. Our superiority over the latest methods justifies our
effectiveness.