Adaptive multi-scale analysis for point-based surface editing

• Published in: Computer graphics forum Vol. 33; no. 7; pp. 171 - 179
• Main Authors: Nader, G., Guennebaud, G., Mellado, N.
• Format: Journal Article
• Language: English
• Published: Oxford Blackwell Publishing Ltd 01.10.2014; Wiley
• Subjects: Analysis; Artificial intelligence; Categories and Subject Descriptors (according to ACM CCS); Computer graphics; Computer Science; Graphics; I.3.3 [Computer Graphics]: Picture/Image Generation-Line and curve generation; Studies; Topological manifolds
• ISSN: 0167-7055; 1467-8659; 1467-8659
• DOI: 10.1111/cgf.12485

This paper presents a tool that enables the direct editing of surface features in large point‐clouds or meshes. This is made possible by a novel multi‐scale analysis of unstructured point‐clouds that automatically extracts the number of relevant features together with their respective scale all over the surface. Then, combining this ingredient with an adequate multi‐scale decomposition allows us to directly enhance or reduce each feature in an independent manner. Our feature extraction is based on the analysis of the scale‐variations of locally fitted surface primitives combined with unsupervised learning techniques. Our tool may be applied either globally or locally, and millions of points are handled in real‐time. The resulting system enables users to accurately edit complex geometries with minimal interaction.