Publications by Miguel Amável Dos Santos Pinheiro

Geometric Graph Matching Using Monte Carlo Tree Search

Pascal Fua, Jan Kybic, Miguel Amável Dos Santos Pinheiro

We present an efficient matching method for generalized geometric graphs. Such graphs consist of vertices in space connected by curves and can represent many real world structures such as road networks in remote sensing, or vessel networks in medical imagi ...

Ieee Computer Soc2017

Reconstructing Evolving Tree Structures in Time Lapse Sequences by Enforcing Time-Consistency

Pascal Fua, Engin Türetken, Raphael Sznitman, Jan Kybic, Agata Justyna Mosinska, Przemyslaw Rafal Glowacki, Miguel Amável Dos Santos Pinheiro, Daniel Lebrecht

We propose a novel approach to reconstructing curvilinear tree structures evolving over time, such as road networks in 2D aerial images or neural structures in 3D microscopy stacks acquired in vivo. To enforce temporal consistency, we simultaneously proces ...

2017

Non-Rigid Graph Registration using Active Testing Search

Pascal Fua, Raphael Sznitman, Jan Kybic, Miguel Amável Dos Santos Pinheiro

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 similarity nor does require a good init ...

Institute of Electrical and Electronics Engineers2015

Reconstructing Evolving Tree Structures in Time Lapse Sequences

Pascal Fua, Engin Türetken, Raphael Sznitman, Jan Kybic, Przemyslaw Rafal Glowacki, Miguel Amável Dos Santos Pinheiro, Daniel Lebrecht

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, we do so for all images simultaneous ...

2014

Active Testing Search for Point Cloud Matching

Pascal Fua, Raphael Sznitman, Jan Kybic, Miguel Amável Dos Santos Pinheiro

We present a general approach for solving the point-cloud matching problem for the case of mildly nonlinear transformations. Our method quickly finds a coarse approximation of the solution by exploring a reduced set of partial matches using an approach to ...

2013