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Robust non-rigid registration of 2D and 3D graphs
Serradell, Eduard; Glowacki, Przemyslaw; Jan, Kybic; Moreno-Noguer, Francesc; Fua, Pascal
Universitat Politècnica de Catalunya. Institut de Robòtica i Informàtica Industrial; Universitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel.ligents
We present a new approach to matching graphs embedded in R2 or R3. Unlike earlier methods, our approach does not rely on the similarity of local appearance features, does not require an initial alignment, can handle partial matches, and can cope with non-linear deformations and topological differences. To handle arbitrary non-linear deformations, we represent them as Gaussian Processes. In the absence of appearance information, we iteratively establish correspondences between graph nodes, update the structure accordingly, and use the current mapping estimate to find the most likely correspondences that will be used in the next iteration. This makes the computation tractable. We demonstrate the effectiveness of our approach first on synthetic cases and then on angiography data, retinal fundus images, and microscopy image stacks acquired at very different resolutions.
Peer Reviewed
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo
Computer vision
computer vision Author keywords: deformable models
medical imaging
graph matching
Visió per ordinador
Classificació INSPEC::Pattern recognition::Computer vision
Attribution-NonCommercial-NoDerivs 3.0 Spain

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