KAUST DepartmentComputer Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Visual Computing Center (VCC)
KAUST Grant NumberOCRF-2014-CRG3-62140401
Preprint Posting Date2017-04-30
Online Publication Date2018-03-05
Print Publication Date2018
Permanent link to this recordhttp://hdl.handle.net/10754/626556
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AbstractWe 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.
CitationAlgarni 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.
SponsorsThis work was supported by KAUST OCRF-2014-CRG3-62140401, and the Visual Computing Center at KAUST.