Curve Reconstruction from Noisy and Unordered Samples
Marek W. Rupniewski · 2014
An algorithm for the reconstruction of closed and open curves from clouds of their noisy and unordered samples is presented. Each curve is reconstructed as a polygonal path represented by its vertices, which are determined in an iterative process comprising evolutionary and decimation stages. The quality of the reconstruction is studied with respect to the local density of the samples and the standard deviation of the noise perturbing the samples. The algorithm is verified to work for arbitrary dimensions of ambient space.