Surface Reconstruction from Scattered Point via RBF Interpolation on GPU

TL;DR

This paper presents a GPU-accelerated parallel method using radial basis functions for efficient and accurate surface reconstruction from scattered points, overcoming traditional computational challenges.

Contribution

It introduces a GPU-based parallel implementation of RBF surface reconstruction, significantly improving computational efficiency while maintaining accuracy.

Findings

High reconstruction accuracy achieved

Significant reduction in computation time on GPU

Effective use of parallel scientific libraries

Abstract

In this paper we describe a parallel implicit method based on radial basis functions (RBF) for surface reconstruction. The applicability of RBF methods is hindered by its computational demand, that requires the solution of linear systems of size equal to the number of data points. Our reconstruction implementation relies on parallel scientific libraries and is supported for massively multi-core architectures, namely Graphic Processor Units (GPUs). The performance of the proposed method in terms of accuracy of the reconstruction and computing time shows that the RBF interpolant can be very effective for such problem.