Complementary Space for Enhanced Uncertainty and Dynamics Visualization

TL;DR

This paper introduces a method to visualize and quantify the hidden topological features of 3D models, such as tunnels and voids, to better understand the effects of local uncertainties and modifications on shape structure.

Contribution

It presents a novel approach for computing and visualizing complementary topological features of 3D shapes, aiding in understanding the impact of local errors and deformations.

Findings

Complementary features reveal effects of local uncertainty.

Visualization aids in understanding shape structure and function.

Method enhances analysis of hierarchical and dynamic models.

Abstract

Given a computer model of a physical object, it is often quite difficult to visualize and quantify any global effects on the shape representation caused by local uncertainty and local errors in the data. This problem is further amplified when dealing with hierarchical representations containing varying levels of detail and / or shapes undergoing dynamic deformations. In this paper, we compute, quantify and visualize the complementary topological and geometrical features of 3D shape models, namely, the tunnels, pockets and internal voids of the object. We find that this approach sheds a unique light on how a model is affected by local uncertainty, errors or modifications and show how the presence or absence of complementary shape features can be essential to an object's structural form and function.