In the Search for Good Neck Cuts
Sam Ruggerio, Sariel Har-Peled
TL;DR
The paper tackles the problem of extracting neck-like features on genus-zero surfaces by formalizing bottlenecks as high-tightness cuts within an isoperimetric framework. It introduces a practical, shortest-path–based algorithm that avoids heavy preprocessing and achieves sub-quadratic runtimes in real meshes, underpinned by a polynomial-time approximation for the collar under well-behavedness assumptions. Key contributions include a formal tightness/alpha-bottleneck notion, a scalable pipeline for salient-point detection, and a skeleton-driven search for high-quality neck-curves, with empirical validation on standard 3D mesh datasets. The approach yields a simple, implementable method that produces locally near-optimal neck cuts, offering improvements over topological and algebraic methods while remaining practical for robotics, mesh segmentation, and related applications.
Abstract
We study the problem of finding neck-like features on a surface. Applications for such cuts include robotics, mesh segmentation, and algorithmic applications. We provide a new definition for a surface bottleneck -- informally, it is the shortest cycle relative to the size of the areas it separates. Inspired by the isoperimetric inequality, we formally define such optimal cuts, study their properties, and present several algorithms inspired by these ideas that work surprisingly well in practice. For examples of our algorithms, see https://neckcut.space.
