By Topic

Surface curvature estimation from the signed distance field

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
T. Masuda ; Intelligent Syst. Inst., Nat. Inst. of Adv. Ind. Sci. & Technol., Ibaraki, Japan

We propose a method of computing surface curvature properties from the signed distance field (SDF) samples in the 3D space. The SDF representation contains information of the surface normal at the closest point on the surface from the sampling point. The variance of these information from different sampling points within the neighborhood reflects the curvature information. Because this sampling is done in the 3D space, we do not directly referees to the parametric surface coordinates or polygon structures. The computation is stable because it requires only linear algebraic operations. It is possible to extract multiple scale curvatures by changing sampling interval. The proposed method was applied on real data, and result of multiscale curvature extraction is presented.

Published in:

3-D Digital Imaging and Modeling, 2003. 3DIM 2003. Proceedings. Fourth International Conference on

Date of Conference:

6-10 Oct. 2003