Quadtree- and octree-based approach for point data selection in 2D or 3D

Abstract

This article describes a new automatic quadtree-/octree-based and scale-dependent generalization algorithm for point selection. The benefit toward existing point selection methods is that it preserves global as well as local characteristics of the spatial point distribution and of the spatial point density. It can be applied not only to points in 2D space but also to points in 3D space. In this article, an evaluation of the new point selection method is also provided.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 18 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.