Publications de Pascal Fua | EPFL Graph Search

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Observable Subspaces for 3D Human Motion Recovery

Pascal Fua, Mathieu Salzmann, Andrea Fossati

The articulated body models used to represent human motion typically have many degrees of freedom, usually expressed as joint angles that are highly correlated. The true range of motion can therefore be represented by latent variables that span a low-dimen ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009

EPnP: An Accurate O(n) Solution to the PnP Problem

Pascal Fua, Vincent Lepetit

We propose a non-iterative solution to the PnP problem-the estimation of the pose of a calibrated camera from n 3D-to-2D point correspondences-whose computational complexity grows linearly with n. This is in contrast to state-of-the-art methods that are O( ...

Springer Verlag2009

Compact Signatures for High-speed Interest Point Description and Matching

Pascal Fua, Vincent Lepetit, Michael Calonder

Prominent feature point descriptors such as SIFT and SURF allow reliable real-time matching but at a computational cost that limits the number of points that can be handled on PCs, and even more on less powerful mobile devices. A recently proposed techniqu ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009

Training for Task Specific Keypoint Detection

Pascal Fua, Christoph Strecha, Albrecht Johannes Lindner, Karim Ali

In this paper, we show that a better performance can be achieved by training a keypoint detector to only find those points that are suitable to the needs of the given task. We demonstrate our approach in an urban environment, where the keypoint detector sh ...

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2009

Capturing 3D Stretchable Surfaces from Single Images in Closed Form

Pascal Fua, Mathieu Salzmann, Vincent Lepetit

We present a closed-form solution to the problem of re- covering the 3D shape of a non-rigid potentially stretchable surface from 3D-to-2D correspondences. In other words, we can reconstruct a surface from a single image without a priori knowledge of its d ...

2009

Steerable Features for Statistical 3D Dendrite Detection

Michaël Unser, Pascal Fua, François Fleuret, François Aguet

Most state-of-the-art algorithms for filament detection in 3-D image-stacks rely on computing the Hessian matrix around individual pixels and labeling these pixels according to its eigenvalues. This approach, while very effective for clean data in which li ...

Springer2009

A fast local descriptor for dense matching

Pascal Fua, Vincent Lepetit, Engin Tola

We introduce a novel local image descriptor designed for dense wide-baseline matching purposes. We feed our descriptors to a graph-cuts based dense depth map estimation algorithm and this yields better wide-baseline performance than the commonly used corre ...

2008

Principled Detection-by-Classification from Multiple Views

Pascal Fua, François Fleuret, Jérôme Berclaz

Machine-learning based classification techniques have been shown to be effective at detecting objects in complex scenes. However, the final results are often obtained from the alarms produced by the classifiers through a post-processing which typically rel ...

2008

Pascal Fua

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Observable Subspaces for 3D Human Motion Recovery

EPnP: An Accurate O(n) Solution to the PnP Problem

Compact Signatures for High-speed Interest Point Description and Matching

Training for Task Specific Keypoint Detection

Capturing 3D Stretchable Surfaces from Single Images in Closed Form

Steerable Features for Statistical 3D Dendrite Detection

Tracking Articulated Bodies using Generalized Expectation Maximization

Retrieving multiple light sources in the presence of specular reflections and texture

A fast local descriptor for dense matching

Principled Detection-by-Classification from Multiple Views

EPnP: An Accurate O(n) Solution to the PnP Problem

Tracking Articulated Bodies using Generalized Expectation Maximization

A fast local descriptor for dense matching

Observable Subspaces for 3D Human Motion Recovery

Steerable Features for Statistical 3D Dendrite Detection

Training for Task Specific Keypoint Detection

Principled Detection-by-Classification from Multiple Views

Retrieving multiple light sources in the presence of specular reflections and texture

Compact Signatures for High-speed Interest Point Description and Matching

Capturing 3D Stretchable Surfaces from Single Images in Closed Form