Name
Abstract | ||
|---|---|---|
In this paper we present a new method for alignment of 3D models. This approach is based on symmetry properties, and uses the fact that the principal components analysis (PCA) have good properties with respect to the planar reflective symmetry. The fast search of the best optimal alignment axes within the PCA-eigenvectors is an essential first step in our alignment process. The plane reflection symmetry is used as a criterion for selection. This pre-processing transforms the alignment problem into an indexing scheme based on the number of the retained PCA-axes. We also introduce a local translational invariance cost (LTIC) that captures a measure of the local translational symmetries of a shape with respect to a given direction. Experimental results show that the proposed method finds the rotation that best aligns a 3D mesh. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/SMI.2008.4547969 | Shape Modeling International |
Keywords | Field | DocType |
eigenvalues and eigenfunctions,principal component analysis,search problems,solid modelling,symmetry,3D model alignment,PCA-eigenvector,indexing scheme,local translational invariance cost,optimal alignment axes,planar reflective symmetry,pre-processing transform,principal component analysis,search method,I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling—Curve, surface, solid and object representations | Reflection symmetry,Computer vision,Normalization (statistics),Polygon mesh,Invariant (physics),Algorithm,Search engine indexing,Planar,Artificial intelligence,Solid modeling,Principal component analysis,Mathematics | Conference |
ISBN | Citations | PageRank |
978-1-4244-2261-6 | 12 | 0.62 |
References | Authors | |
17 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohamed Chaouch | 1 | 12 | 0.62 |
| Anne Verroust-blondet | 2 | 12 | 0.62 |