Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Polygonization of implicit surfaces
Computer Aided Geometric Design
Using partial derivatives of 3D images to extract typical surface features
Computer Vision and Image Understanding
New feature points based on geometric invariants for 3D image registration
International Journal of Computer Vision
3D Face Modeling from Stereo and Differential Constraints
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Fast and robust detection of crest lines on meshes
Proceedings of the 2005 ACM symposium on Solid and physical modeling
Line drawings from volume data
ACM SIGGRAPH 2005 Papers
Feature-Preserving Mesh Denoising via Bilateral Normal Filtering
CAD-CG '05 Proceedings of the Ninth International Conference on Computer Aided Design and Computer Graphics
Terrain Synthesis from Digital Elevation Models
IEEE Transactions on Visualization and Computer Graphics
Smooth feature lines on surface meshes
SGP '05 Proceedings of the third Eurographics symposium on Geometry processing
Fast, robust, and faithful methods for detecting crest lines on meshes
Computer Aided Geometric Design
Isosurface Extraction of Volumetric Data Using Implicit Surface Polygonization
AMS '09 Proceedings of the 2009 Third Asia International Conference on Modelling & Simulation
Procedural image processing for visualization
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
| Hi-index | 0.00 |
Crest lines are one of the many types of feature lines that illustrate the prominent characteristics of an object's surface. In this study, we investigate one vital component to extract crest lines, the gradient of the maximal curvature. Most of geometry properties required to calculate crest lines can be obtained from the volume data during the process of the surface construction using implicit surface polygonizer. Nevertheless the gradient of the maximal curvature cannot be obtained due to the nature of the surface construction algorithm. Hence we proposed three weight function based methods in accordance with the knowledge of the surface mesh. We implemented our methods and conducted both qualitative and quantitative analysis on our methods to find the most appropriate method. We also put forward a simple filtering mechanism as a post-processing procedure to enhance the accuracy of the crest lines, which is addressed at the end of this study.