Abstract
We present a new method of extracting multi-scale salient features on meshes. It is based on robust estimation of curvature on multiple scales. The coincidence between salient feature and the scale of interest can be established straightforwardly, where detailed feature appears on small scale and feature with more global shape information shows up on large scale. We demonstrate this multi-scale description of features accords with human perception and can be further used for several applications as feature classification and viewpoint selection. Experiments exhibit that our method as a multi-scale analysis tool is very helpful for studying 3D shapes. © 2012 Springer-Verlag.
Original language | English (US) |
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Title of host publication | Lecture Notes in Computer Science |
Publisher | Springer Nature |
Pages | 122-129 |
Number of pages | 8 |
ISBN (Print) | 9783642342622 |
DOIs | |
State | Published - 2012 |
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science