Prohlížení Publikační činnost - 13133 dle autora "Fua, Pascal"

Zobrazují se záznamy 1-5 z 5

    • Active Testing Search for Point Cloud Matching 

      Autor: Amável Pinheiro, Miguel; Sznitman, Raphael; Serradell, Eduard; Kybic, Jan; Moreno-Noguer, Francesc; Fua, Pascal
      (Springer, 2013)
      We present a general approach for solving the point-cloud matching problem for the case of mildly nonlinear transformations. Our method quickly nds a coarse approximation of the solution by exploring a reduced set of ...

    • Non-Rigid Graph Registration using Active Testing Search 

      Autor: Serradell, Eduard; Amável Pinheiro, Miguel; Sznitman, Raphael; Kybic, Jan; Moreno-Noguer, Francesc; Fua, Pascal
      (2014)
      We present a new approach for matching sets of branching curvilinear structures that form graphs embedded in R2 or R3 and may be subject to deformations. Unlike earlier methods, ours does not rely on local appearance ...

    • Reconstructing Evolving Tree Structures in Time Lapse Sequences 

      Autor: Głowacki, Przemysław; Amável Pinheiro, Miguel; Türetken, Engin; Sznitman, Raphael; Lebrecht, Daniel; Kybic, Jan; Holtmaat, Anthony; Fua, Pascal
      (2014)
      We propose an approach to reconstructing tree structures that evolve over time in 2D images and 3D image stacks such as neuronal axons or plant branches. Instead of reconstructing structures in each image independently, ...

    • Robust elastic 2D/3D geometric graph matching 

      Autor: Serradell, Eduard; Kybic, Jan; Moreno-Noguer, Francesc; Fua, Pascal
      (SPIE, 2012)
      We present an algorithm for geometric matching of graphs embedded in 2D or 3D space. It is applicable for registering any graph-like structures appearing in biomedical images, such as blood vessels, pulmonary bronchi, nerve ...

    • Robust Non-Rigid Registration of 2D and 3D Graphs 

      Autor: Serradell, Eduard; Glowacki, Przemyslaw; Kybic, Jan; Moreno-Noguer, Francesc; Fua, Pascal
      (IEEE, 2012)
      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 ...