Rotation invariant spherical harmonic representation of 3D shape descriptors
Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing
A Theoretical and Computational Framework for Isometry Invariant Recognition of Point Cloud Data
Foundations of Computational Mathematics
Facial Shape-from-shading and Recognition Using Principal Geodesic Analysis and Robust Statistics
International Journal of Computer Vision
Weighted principal geodesic analysis for facial gender classification
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
| Hi-index | 0.00 |
The paper presents a novel method for 3D facial shape recognition. Our inputs are 3D facial shapes which are reconstructed from point clouds, and then filtered using PCA. The resulting data are represented by simplicial complexes. This representation can capture topological and geometric information at a specified resolution with a small number of control points. We calculate the Gromov-Hausdorff distance between simplicial complexes, and this measures how far each pair of faces are from being isometric. Finally, we demonstrate our method in an application to point clouds collected from laser range scanner.