Figure 1: We introduce connectivity editing operations to control irregular vertices in quadrilateral meshes. This can lead to improved results in the design of a glass structure: (a) top: the original mesh with irregular vertices as colored dots, (a) bottom: a stripe pattern applied to the mesh, (b) a rendering of the design as glass construction. In (c) and (d) we show the edited mesh. The glass panels on the roof are generated from the edges in the meshes. AbstractWe propose new connectivity editing operations for quadrilateral meshes with the unique ability to explicitly control the location, orientation, type, and number of the irregular vertices (valence not equal to four) in the mesh while preserving sharp edges. We provide theoretical analysis on what editing operations are possible and impossible and introduce three fundamental operations to move and re-orient a pair of irregular vertices. We argue that our editing operations are fundamental, because they only change the quad mesh in the smallest possible region and involve the fewest irregular vertices (i.e., two). The irregular vertex movement operations are supplemented by operations for the splitting, merging, canceling, and aligning of irregular vertices. We explain how the proposed highlevel operations are realized through graph-level editing operations such as quad collapses, edge flips, and edge splits. The utility of these mesh editing operations are demonstrated by improving the connectivity of quad meshes generated from state-of-art quadrangulation techniques.
We describe an interactive editing framework that provides control over the type, location, and number of irregular vertices in a triangle mesh. We first provide a theoretical analysis to identify the simplest possible operations for editing irregular vertices and then introduce a hierarchy of editing operations to control the type, location, and number of irregular vertices. We demonstrate the power of our editing framework with an example application in pattern design on surfaces.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.