Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
440391 | Computer-Aided Design | 2009 | 12 Pages |
Abstract
This paper presents nn-dimensional feature recognition of triangular meshes that can handle both geometric properties and additional attributes such as color information of a physical object. Our method is based on a tensor voting technique for classifying features and integrates a clustering and region growing methodology for segmenting a mesh into sub-patches. We classify a feature into a corner, a sharp edge and a face. Then, finally we detect features via region merging and cleaning processes. Our feature detection shows good performance with efficiency for various dimensional models.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Graphics and Computer-Aided Design
Authors
Hyun Soo Kim, Han Kyun Choi, Kwan H. Lee,