This work makes a detailed analysis on why using mesh PCA for coordinate direction normalization is always uncertainty in 3D surface registration. Our analysis takes the view of discrete signal statistical analyzing and is based on the specific process research of mesh PCA. Then we present a corrected method to improve mesh PCA effects. Such corrected method comes from the fact that the principal axes directions of 3D surface should be those in which the vertex distances are the longest among all 3D vertex distances. Corresponding experimental results on range scan data and synthetic models are provided.
- Coordinate direction normalization
- Mesh PCA
- Surface registration
ASJC Scopus subject areas
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence