Publications by Andrea Fossati

Efficient Model-free Anthropometry from Depth Data

2017

Real-time vehicle tracking for driving assistance

Pascal Fua, Patrick Merryl Marlon Schönmann, Andrea Fossati

Detecting car taillights at night is a task which can nowadays be accomplished very fast on cheap hardware. We rely on such detections to build a vision-based system that, coupling them in a rule-based fashion, is able to detect and track vehicles. This al ...

2011

Bridging the Gap between Detection and Tracking for 3D Human Motion Recovery

Andrea Fossati

The aim of this thesis is to build a system able to automatically and robustly track human motion in 3–D starting from monocular input. To this end two approaches are introduced, which tackle two different types of motion: The first is useful to analyze ac ...

EPFL2010

From Canonical Poses to 3D Motion Capture Using a Single Camera

Pascal Fua, Vincent Lepetit, Andrea Fossati, Miodrag Dimitrijevic

We combine detection and tracking techniques to achieve robust 3D motion recovery of people seen from arbitrary viewpoints by a single and potentially moving camera. We rely on detecting key postures, which can be done reliably, using a motion model to inf ...

Institute of Electrical and Electronics Engineers2010

Large occlusion completion using normal maps

Pascal Fua, Christoph Strecha, Engin Tola, Andrea Fossati

Dense disparity maps can be computed from wide-baseline stereo pairs but will inevitably contain large areas where the depth cannot be estimated accurately because the pixels are seen in one view only. A traditional approach to this problem is to introduce ...

2010

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

Tracking Articulated Bodies using Generalized Expectation Maximization

Pascal Fua, Andrea Fossati

A generalized expectation maximization (GEM) algorithm is used to retrieve the pose of a person from a monocular video sequence shot with a moving camera. After embedding the set of possible poses in a low dimensional space using principal component analys ...

2008

Linking Pose and Motion

Pascal Fua, Andrea Fossati

Algorithms designed to estimate 3D pose in video sequences enforce temporal consistency but typically overlook an important source of information: The 3D pose of an object, be it rigid or articulated, has a direct influence on its direction of travel. In t ...

2008

Bridging the Gap between Detection and Tracking for 3D Monocular Video-Based Motion Capture

Pascal Fua, Vincent Lepetit, Andrea Fossati, Miodrag Dimitrijevic

We combine detection and tracking techniques to achieve robust 3-D motion recovery of people seen from arbitrary viewpoints by a single and potentially moving camera. We rely on detecting key postures, which can be done reliably, using a motion model to in ...

2007