Type
ArticleKAUST Department
Computer Science ProgramComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Visual Computing Center (VCC)
KAUST Grant Number
OCRF-2014-CRG3-62140401Date
2018-03-05Preprint Posting Date
2017-04-30Online Publication Date
2018-03-05Print Publication Date
2018Permanent link to this record
http://hdl.handle.net/10754/626556
Metadata
Show full item recordAbstract
We present SurfCut, an algorithm for extracting a smooth, simple surface with an unknown 3D curve boundary from a noisy image and a seed point. Our method is built on the novel observation that certain ridge curves of a function defined on a front propagated using the Fast Marching algorithm lie on the surface. Our method extracts and cuts these ridges to form the surface boundary. Our surface extraction algorithm is built on the novel observation that the surface lies in a valley of the distance from Fast Marching. We show that the resulting surface is a collection of minimal paths. Using the framework of cubical complexes and Morse theory, we design algorithms to extract these critical structures robustly. Experiments on three 3D datasets show the robustness of our method, and that it achieves higher accuracy with lower computational cost than state-of-the-art.Citation
Algarni M, Sundaramoorthi G (2018) SurfCut: Surfaces of Minimal Paths From Topological Structures. IEEE Transactions on Pattern Analysis and Machine Intelligence: 1–1. Available: http://dx.doi.org/10.1109/TPAMI.2018.2811810.Sponsors
This work was supported by KAUST OCRF-2014-CRG3-62140401, and the Visual Computing Center at KAUST.arXiv
arXiv:1705.00301Additional Links
http://arxiv.org/abs/1705.00301v1http://arxiv.org/pdf/1705.00301v1
http://ieeexplore.ieee.org/document/8306823/
ae974a485f413a2113503eed53cd6c53
10.1109/TPAMI.2018.2811810