SOURCE-LINKED INTELLIGENCE

Gaussian Linear Functional Manifold Method for Massive Point Cloud Data

arXiv · AI, language, vision and robotics · article · Sep 4, 2026 · UTC

Reconstructing continuous terrain manifolds from massive, unstructured airborne LiDAR point clouds remains challenging in complex Wildland-Urban Interface (WUI) environments, where deep neural networks require costly point-wise annotations and nonparametric surface reconstruction methods often lack structural interpretability. This paper introduces the Gaussian Linear Functional Manifold (GLFM), a physics-informed statistical framework that represents continuous surface topography using deterministic linear functional bases while modeling microscale diffuse laser backscatter as an isotropic Ga

Read original source ↗ Open in workspace

recordType

paper

region

Global