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Separatrix Persistence: Extraction of Salient Edges on Surfaces Using Topological Methods Corresponding Publication
Logo Salient edges are perceptually prominent features of a surface. Most previous extraction schemes utilize the notion of ridges and valleys for their detection, thereby requiring curvature derivatives which are rather sensitive to noise. We introduce a novel method for salient edge extraction which does not depend on curvature derivatives. It is based on a topological analysis of the principal curvatures and salient edges of the surface are identified as parts of separatrices of the topological skeleton. Previous topological approaches obtain results including non-salient edges due to inherent properties of the underlying algorithms. We extend the profound theory by introducing the novel concept of separatrix persistence, which is a smooth measure along a separatrix and allows to keep its most salient parts only. We compare our results with other methods for salient edge extraction. T. Weinkauf, D. Günther
Separatrix Persistence: Extraction of Salient Edges on Surfaces Using Topological Methods
Computer Graphics Forum (Proc. SGP '09) 28(5), July 2009
[slideshow]
Salient edges of the screwdriver model. Red denotes convex edges, blue concave edges. Cover image of SGP09 Proceedings.
Salient edges of the screwdriver model. Red denotes convex edges, blue concave edges. Cover image of SGP09 Proceedings.
Salient edges of the dino model have been extracted as separatrices of the topological skeletons of the principal curvatures. Cover image of SGP09 Proceedings.
Salient edges of the dino model have been extracted as separatrices of the topological skeletons of the principal curvatures. Cover image of SGP09 Proceedings.
Salient edges of the knot model. The most salient edges have been identified using separatrix persistence. Cover image of SGP09 Proceedings.
Salient edges of the knot model. The most salient edges have been identified using separatrix persistence. Cover image of SGP09 Proceedings.
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