Interactive Design of Developable Surfaces by Patch-based Learning

An optional description of the image for screen readers. By Caigui Jiang

Abstract

This paper introduces an interactive design method for developable surfaces, centered on a datadriven approach to optimize surface patches for developability. Surface patches are the fundamental components of an entire surface, typically represented by triangular meshes. We propose a novel learning-based method that effectively transforms patches with arbitrary boundaries into their closest developable surfaces. Based on this method, our tools enable real-time, drag-and-drop design of developable surfaces and support piecewise developable approximation through interactive inputs. Experimental results demonstrate that this method provides a fast computational foundation for the interactive design of developable surfaces, enhancing design flexibility while exhibiting excellent robustness and generalization. The piecewise developable approximation of the model, guided by human-computer collaborative segmentation, achieved higher overall approximation accuracy, fewer patches, and lifelike papercraft outcomes. This offers greater flexibility to meet the application requirements of complex real-world scenarios and provides a new paradigm for integrating deep learning with interactive geometry design.

Publication
Computer-Aided Design
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Chaoyun Wang 王超运
Chaoyun Wang 王超运
Ph.D Student

My current research topic is intelligent optimization and application of developable surfaces, which use deep learning methods to solve geometric optimization problems, and apply geometric constraint properties to computer vision tasks.

Jianlei Wang 王建磊
Jianlei Wang 王建磊
Ph.D Student

My research interests are in geometry processing, AI-driven design, 3D fabrication and computer graphics.

Caigui Jiang
Caigui Jiang
Professor

My research interests are in geometric modeling, geometry processing, architectural geometry, computer graphics, and computer vision.