Computational schemes for biomimetic sculpture
Proceedings of the 5th conference on Creativity & cognition
The Medial Scaffold of 3D Unorganized Point Clouds
IEEE Transactions on Pattern Analysis and Machine Intelligence
A mean field annealing approach to accurate free form shape matching
Pattern Recognition
Replicator Dynamics in the Iterative Process for Accurate Range Image Matching
International Journal of Computer Vision
Surface reconstruction from point clouds by transforming the medial scaffold
Computer Vision and Image Understanding
Measuring 3D shape similarity by graph-based matching of the medial scaffolds
Computer Vision and Image Understanding
Surface registration markers from range scan data
IWCIA'06 Proceedings of the 11th international conference on Combinatorial Image Analysis
A validation benchmark for assessment of medial surface quality for medical applications
ICVS'13 Proceedings of the 9th international conference on Computer Vision Systems
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This paper proposes a novel method for global registration based on matching 3D medial structures of unorganized point clouds or triangulated meshes. Most practical known methods are based on the Iterative Closest Point (ICP) algorithm, which requires an initial alignment close to the globally optimal solution to ensure convergence to a valid solution. Furthermore, it can also fail when there are points in one dataset with no corresponding matches in the other dataset. The proposed method automatically finds an initial alignment close to the global optimal by using the medial structure of the datasets. For this purpose, we first compute the medial scaffold of a 3D dataset: a 3D graph made of special shock curves linking special shock nodes. This medial scaffold is then regularized exploiting the known transitions of the 3D medial axis under deformation or perturbation of the input data. The resulting simplified medial scaffolds are then registered using a modified graduated assignment graph matching algorithm. The proposed method shows robustness to noise, shape deformations, and varying surface sampling densities.