Patternshop: Editing Point Patterns by Image Manipulation

TL;DR

Patternshop introduces a novel low-dimensional embedding for point pattern correlation, enabling intuitive editing via image manipulation tools and supporting diverse applications like recoloring and texture synthesis.

Contribution

It provides the first compact representation for spatially-varying correlation in point patterns, facilitating intuitive editing with standard image software.

Findings

Effective manipulation of point patterns demonstrated

User experiments confirm usability and effectiveness

Supports diverse editing tasks like recoloring and texture synthesis

Abstract

Point patterns are characterized by their density and correlation. While spatial variation of density is well-understood, analysis and synthesis of spatially-varying correlation is an open challenge. No tools are available to intuitively edit such point patterns, primarily due to the lack of a compact representation for spatially varying correlation. We propose a low-dimensional perceptual embedding for point correlations. This embedding can map point patterns to common three-channel raster images, enabling manipulation with off-the-shelf image editing software. To synthesize back point patterns, we propose a novel edge-aware objective that carefully handles sharp variations in density and correlation. The resulting framework allows intuitive and backward-compatible manipulation of point patterns, such as recoloring, relighting to even texture synthesis that have not been available to 2D point pattern design before. Effectiveness of our approach is tested in several user experiments.