Name
Abstract | ||
|---|---|---|
In this paper, we propose a novel method to register images defined on spherical meshes. Instances of such spherical images include inflated cortical feature maps in brain medical imaging or images from omni directional cameras. We apply the Geodesic Active Fields (GAF) framework locally at each vertex of the mesh. Therefore we define a dense deformation field, which is embedded in a higher dimensional manifold, and minimize the weighted Polyakov energy. While the Polyakov energy itself measures the hyper area of the embedded deformation field, its weighting allows to account for the quality of the current image alignment. Iteratively minimizing the energy drives the deformation field towards a smooth solution of the registration problem. Although the proposed approach does not necessarily outperform state-of-the-art methods that are tightly tailored to specific applications, it is of methodological interest due to its high degree of flexibility and versatility. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICPR.2010.1089 | Pattern Recognition |
Keywords | Field | DocType |
polyakov energy,deformation field,brain medical imaging,cortical feature map,spherical mesh,spherical image,embedded deformation field,weighted polyakov energy,dense deformation field,active fields,sphere,noise reduction,minimization,pde,surfaces,mesh generation,image registration,gradient descent,embedding,spheres,cortex,diffusion equation,computational geometry,feature extraction,manifolds,differential geometry,regularization,scale space,manifold | Spherical image,Topology,Computer vision,Polygon mesh,Computer science,Computational geometry,Feature extraction,Artificial intelligence,Geodesic,Manifold,Image registration,Mesh generation | Conference |
ISSN | ISBN | Citations |
1051-4651 | 978-1-4244-7542-1 | 1 |
PageRank | References | Authors |
0.35 | 10 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dominique Zosso | 1 | 273 | 16.60 |
| Jean-Philippe Thiran | 2 | 2320 | 257.56 |