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of 81
pro vyhledávání: '"Lüthi, Marcel"'
In this paper, we unify popular non-rigid registration methods for point sets and surfaces under our general framework, GiNGR. GiNGR builds upon Gaussian Process Morphable Models (GPMM) and hence separates modeling the deformation prior from model ad
Externí odkaz:
http://arxiv.org/abs/2203.09986
Autor:
Fouefack, Jean-Rassaire, Borotikar, Bhushan, Lüthi, Marcel, Douglas, Tania S., Burdin, Valérie, Mutsvangwa, Tinashe E. M.
In model-based medical image analysis, three features of interest are the shape of structures of interest, their relative pose, and image intensity profiles representative of some physical property. Often, these are modelled separately through statis
Externí odkaz:
http://arxiv.org/abs/2112.04495
Autor:
Madsen, Dennis, Morel-Forster, Andreas, Kahr, Patrick, Rahbani, Dana, Vetter, Thomas, Lüthi, Marcel
We propose to view non-rigid surface registration as a probabilistic inference problem. Given a target surface, we estimate the posterior distribution of surface registrations. We demonstrate how the posterior distribution can be used to build shape
Externí odkaz:
http://arxiv.org/abs/1907.01414
Autor:
Fouefack, Jean-Rassaire, Borotikar, Bhushan, Lüthi, Marcel, Douglas, Tania S., Burdin, Valérie, Mutsvangwa, Tinashe E.M.
Publikováno v:
In Medical Image Analysis April 2023 85
Autor:
Ebert, Lars C., Rahbani, Dana, Lüthi, Marcel, Thali, Michael J., Christensen, Angi M., Fliss, Barbara
Publikováno v:
In Forensic Science International March 2022 332
Autor:
Gerig, Thomas, Morel-Forster, Andreas, Blumer, Clemens, Egger, Bernhard, Lüthi, Marcel, Schönborn, Sandro, Vetter, Thomas
In this paper, we present a novel open-source pipeline for face registration based on Gaussian processes as well as an application to face image analysis. Non-rigid registration of faces is significant for many applications in computer vision, such a
Externí odkaz:
http://arxiv.org/abs/1709.08398
Statistical shape models (SSMs) represent a class of shapes as a normal distribution of point variations, whose parameters are estimated from example shapes. Principal component analysis (PCA) is applied to obtain a low-dimensional representation of
Externí odkaz:
http://arxiv.org/abs/1603.07254
Autor:
Lüthi, Marcel
Today’s increasing demand for energy and natural resources requires safe and reliable infrastructure. This includes hydraulic earth structures like dikes, levees, or dams. Such structures are susceptible to piping, a fundamental type of internal so
Externí odkaz:
http://hdl.handle.net/2429/36999
Publikováno v:
In Medical Image Analysis December 2013 17(8):959-973
Akademický článek
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