Publication
Fast Projector-Driven Structured Light Matching in Sub-Pixel Accuracy using Bilinear Interpolation Assumption
Torben Fetzer; Gerd Reis; Didier Stricker
In: International Conference on Computer Analysis of Images and Patterns. International Conference on Computer Analysis of Images and Patterns (CAIP-2021), September 27-30, Online, Springer LNCS, 2021.
Abstract
In practical applications where high-precision reconstructions are required,
whether for quality control or damage assessment, structured light reconstruction
is often the method of choice. It allows to achieve dense point correspondences
over the entire scene independently of any object texture. The optimal
matches between images with respect to an encoded surface point are usually
not on pixel but on sub-pixel level. Common matching techniques that look for
pixel-to-pixel correspondences between camera and projector often lead to noisy
results that must be subsequently smoothed. The method presented here allows to
find optimal sub-pixel positions for each projector pixel in a single pass and thus
requires minimal computational effort. For this purpose, the quadrilateral regions
containing the sub-pixels are extracted. The convexity of these quads and their
consistency in terms of topological properties can be guaranteed during runtime.
Subsequently, an explicit formulation of the optimal sub-pixel position within
each quad is derived, using bilinear interpolation, and the permanent existence
of a valid solution is proven. In this way, an easy-to-use procedure arises that
matches any number of cameras in a structured light setup with high accuracy and
low complexity. Due to the ensured topological properties, exceptionally smooth,
highly precise, uniformly sampled matches with almost no outliers are achieved.
The point correspondences obtained do not only have an enormously positive effect
on the accuracy of reconstructed point clouds and resulting meshes, but are
also extremely valuable for auto-calibrations calculated from them.