This paper proposes an efficient and Feature-preserving Locally Optimal Projection operator
(FLOP) for geometry reconstruction. Our operator is bilateral weighted, taking both spatial
and geometric feature information into consideration for feature-preserving approximation.
We then present an accelerated FLOP operator based on the random sampling of the Kernel
Density Estimate (KDE), which produces reconstruction results close to those generated
using the complete point set data, to within a given accuracy. Additionally, we extend our …