EngineeringComputer Science

Efficient surface fitting via randomized Gauss–Seidel LSPIA: a novel iterative approach

Zhenmin Yao, Qianqian Hu

2026.2.1VISUAL COMPUTER

DOI: 10.1007/s00371-025-04266-0

tlooto Summary

A novel randomized Gauss–Seidel LSPIA (RGS-LSPIA) method for efficient surface fitting that mitigates the issue of numerical instability caused by ill-conditioned matrix properties and significantly improves computational efficiency.

Abstract

Abstract is not available.

Citation format

YAO, Zhenmin; HU, Qianqian. Efficient surface fitting via randomized gauss–seidel LSPIA: A novel iterative approach. VISUAL COMPUTER, 2026, 42(3).