Learning to Segment and Unfold Polyhedral Mesh from Failures

Zhonghua Xi and Yun-hyeong Kim and Young J. Kim and Jyh-Ming Lien


Folding planar sheets to make 3D shapes from is an ancient practice with many new applications, ranging from personal fabrication of customized items to design of surgical instruments for minimally invasive surgery in self-folding machines. Given a polyhedral mesh, unfolding is an operation of cutting and flattening the mesh. The flattened polyhedral nets are then cut out of planar materials and folded back to 3D. Unfolding a polyhedral mesh into planar nets usually require segmentation. Either used as a preprocessing step to simplify the mesh and provide semantics or as the result of unfolding to avoid overlapping, the segmentation and the unfolding operations are decoupled. Consequently, segmented components may not be unfoldable and unfolded nets usually provide no semantic meaning and make folding difficult. In this paper, we propose a strategy that tightly couples unfolding and segmentation. We show that the proposed method produces unfoldable segmentation that resembles carefully designed paper craft. The key idea that enables this capability is an algorithm that learns from failed unfoldings.




Learning to Segment and Unfold Polyhedral Mesh from Failures, Zhonghua Xi and Yun-Hyeong Kim and Young J. Kim and Jyh-Ming Lien, Shape Modeling International (SMI); also appears in Journal of Computers & Graphics, Jun. 2016
Web Site / Paper(pdf) / BibTeX


Coming soon



image image

image image

image image

image image

Left: Segmentation Restuls. Right: Paper craft.


Segmentation resutls on Princeton Shape Segmentation Benchmark

Related Works

Origami Research Pages / All Research Pages
Computer Science @ George Mason University